2007-01-31 00:00:00

NIH Lecture: Computation with Information Described in Natural Language (Feb 8)

NIH’s Biomedical Computing Group is putting together a lecture on natural language computation (not to be confused with natural language processing). If you’re interested in attending, drop me a comment here and we can meet up there. The speaker, Dr. Lofti A. Zadeh, prepared the following abstract (see poster):

What is meant by Computation with Information Described in Natural Language, or NL-Computation, for short? Does NL-Computation constitute a new frontier in computation? Do existing bivalent-logic-based approaches to natural language processing provide a basis for NL-Computation? What are the basic concepts and ideas which underlie NL-Computation? These are some of the issues which are addressed in the following.

What is computation with information described in natural language? Here are simple examples. I am planning to drive from Berkeley to Santa Barbara, with stopover for lunch in Monterey. It is about 10 am. It will probably take me about two hours to get to Monterey and about an hour to have lunch. From Monterey, it will probably take me about five hours to get to Santa Barbara. What is the probability that I will arrive in Santa Barbara before about six pm? Another simple example: A box contains about twenty balls of various sizes. Most are large. What is the number of small balls? What is the probability that a ball drawn at random is neither small nor large? Another example: A function, f, from reals to reals is described as: If X is small then Y is small; if X is medium then Y is large; if X is large then Y is small. What is the maximum of f? Another example: Usually the temperature is not very low, and usually the temperature is not very high. What is the average temperature? Another example: Usually most United Airlines flights from San Francisco leave on time. What is the probability that my flight will be delayed?

Computation with information described in natural language is closely related to Computing with Words. NL-Computation is of intrinsic importance because much of human knowledge is described in natural language. This is particularly true in such fields as economics, data mining, systems engineering, risk assessment and emergency management. It is safe to predict that as we move further into the age of machine intelligence and mechanized decision-making, NL-Computation will grow in visibility and importance.

Computation with information described in natural language cannot be dealt with through the use of machinery of natural language processing. The problem is semantic imprecision of natural languages. More specifically, a natural language is basically a system for describing perceptions. Perceptions are intrinsically imprecise, reflecting the bounded ability of sensory organs, and ultimately the brain, to resolve detail and store information. Semantic imprecision of natural languages is a concomitant of imprecision of perceptions.

Our approach to NL-Computation centers on what is referred to as generalized-constraint-based computation, or GC-Computation for short. A fundamental thesis which underlies NL-Computation is that information may be interpreted as a generalized constraint. A generalized constraint is expressed as X isr R, where X is the constrained variable, R is a constraining relation and r is an indexical variable which defines the way in which R constrains X. The principal constraints are possibilistic, veristic, probabilistic, usuality, random set, fuzzy graph and group. Generalized constraints may be combined, qualified, propagated, and counter propagated, generating what is called the Generalized Constraint Language, GCL. The key underlying idea is that information conveyed by a proposition may be represented as a generalized constraint, that is, as an element of GCL.

In our approach, NL-Computation involves three modules: (a) Precisiation module; (b) Protoform module; and (c) Computation module. The meaning of an element of a natural language, NL, is precisiated through translation into GCL and is expressed as a generalized constraint. An object of precisiation, p, is referred to as precisiend, and the result of precisiation, p*, is called a precisiand. Usually, a precisiend is a proposition, a system of propositions or a concept. A precisiend may have many precisiands. Definition is a form of precisiation. A precisiand may be viewed as a model of meaning. The degree to which the intension (attribute-based meaning) of p* approximates to that of p is referred to as cointension. A precisiand, p*, is cointensive if its cointension with p is high, that is, if p* is a good model of meaning of p.

The Protoform module serves as an interface between Precisiation and Computation modules. Basically, its function is that of abstraction and summarization.

The Computation module serves to deduce an answer to a query, q. The first step is precisiation of q, with precisiated query, q*, expressed as a function of n variables u1, ???, un. The second step involves precisiation of query-relevant information, leading to a precisiand which is expressed as a generalized constraint on u1, ???, un. The third step involves an application of the extension principle, which has the effect of propagating the generalized constraint on u1, ???, un to a generalized constraint on the precisiated query, q*. Finally, the constrained q* is interpreted as the answer to the query and is retranslated into natural language.

The generalized-constraint-based computational approach to NL-Computation opens the door to a wide-ranging enlargement of the role of natural languages in scientific theories. Particularly important application areas are decision-making with information described in natural language, economics, systems engineering, risk assessment, qualitative systems analysis, search, question-answering and theories of evidence.

Filed under: — @ 2007-01-31 00:00:00
2007-01-31 00:00:00

NIH Lecture: Computation with Information Described in Natural Language (Feb 8)

NIH’s Biomedical Computing Group is putting together a lecture on natural language computation (not to be confused with natural language processing). If you’re interested in attending, drop me a comment here and we can meet up there. The speaker, Dr. Lofti A. Zadeh, prepared the following abstract (see poster):

What is meant by Computation with Information Described in Natural Language, or NL-Computation, for short? Does NL-Computation constitute a new frontier in computation? Do existing bivalent-logic-based approaches to natural language processing provide a basis for NL-Computation? What are the basic concepts and ideas which underlie NL-Computation? These are some of the issues which are addressed in the following.

What is computation with information described in natural language? Here are simple examples. I am planning to drive from Berkeley to Santa Barbara, with stopover for lunch in Monterey. It is about 10 am. It will probably take me about two hours to get to Monterey and about an hour to have lunch. From Monterey, it will probably take me about five hours to get to Santa Barbara. What is the probability that I will arrive in Santa Barbara before about six pm? Another simple example: A box contains about twenty balls of various sizes. Most are large. What is the number of small balls? What is the probability that a ball drawn at random is neither small nor large? Another example: A function, f, from reals to reals is described as: If X is small then Y is small; if X is medium then Y is large; if X is large then Y is small. What is the maximum of f? Another example: Usually the temperature is not very low, and usually the temperature is not very high. What is the average temperature? Another example: Usually most United Airlines flights from San Francisco leave on time. What is the probability that my flight will be delayed?

Computation with information described in natural language is closely related to Computing with Words. NL-Computation is of intrinsic importance because much of human knowledge is described in natural language. This is particularly true in such fields as economics, data mining, systems engineering, risk assessment and emergency management. It is safe to predict that as we move further into the age of machine intelligence and mechanized decision-making, NL-Computation will grow in visibility and importance.

Computation with information described in natural language cannot be dealt with through the use of machinery of natural language processing. The problem is semantic imprecision of natural languages. More specifically, a natural language is basically a system for describing perceptions. Perceptions are intrinsically imprecise, reflecting the bounded ability of sensory organs, and ultimately the brain, to resolve detail and store information. Semantic imprecision of natural languages is a concomitant of imprecision of perceptions.

Our approach to NL-Computation centers on what is referred to as generalized-constraint-based computation, or GC-Computation for short. A fundamental thesis which underlies NL-Computation is that information may be interpreted as a generalized constraint. A generalized constraint is expressed as X isr R, where X is the constrained variable, R is a constraining relation and r is an indexical variable which defines the way in which R constrains X. The principal constraints are possibilistic, veristic, probabilistic, usuality, random set, fuzzy graph and group. Generalized constraints may be combined, qualified, propagated, and counter propagated, generating what is called the Generalized Constraint Language, GCL. The key underlying idea is that information conveyed by a proposition may be represented as a generalized constraint, that is, as an element of GCL.

In our approach, NL-Computation involves three modules: (a) Precisiation module; (b) Protoform module; and (c) Computation module. The meaning of an element of a natural language, NL, is precisiated through translation into GCL and is expressed as a generalized constraint. An object of precisiation, p, is referred to as precisiend, and the result of precisiation, p*, is called a precisiand. Usually, a precisiend is a proposition, a system of propositions or a concept. A precisiend may have many precisiands. Definition is a form of precisiation. A precisiand may be viewed as a model of meaning. The degree to which the intension (attribute-based meaning) of p* approximates to that of p is referred to as cointension. A precisiand, p*, is cointensive if its cointension with p is high, that is, if p* is a good model of meaning of p.

The Protoform module serves as an interface between Precisiation and Computation modules. Basically, its function is that of abstraction and summarization.

The Computation module serves to deduce an answer to a query, q. The first step is precisiation of q, with precisiated query, q*, expressed as a function of n variables u1, ???, un. The second step involves precisiation of query-relevant information, leading to a precisiand which is expressed as a generalized constraint on u1, ???, un. The third step involves an application of the extension principle, which has the effect of propagating the generalized constraint on u1, ???, un to a generalized constraint on the precisiated query, q*. Finally, the constrained q* is interpreted as the answer to the query and is retranslated into natural language.

The generalized-constraint-based computational approach to NL-Computation opens the door to a wide-ranging enlargement of the role of natural languages in scientific theories. Particularly important application areas are decision-making with information described in natural language, economics, systems engineering, risk assessment, qualitative systems analysis, search, question-answering and theories of evidence.

Filed under: — @ 2007-01-31 00:00:00
2007-01-30 00:00:00

Jasypt: Java encryption library that eases encryption of database fields too

If you’re writing healthcare apps in Java, take a look at Jasypt. Especially if you need to encrypt data in your databases. Here’s how the authors describe it:

Jasypt is a java library which allows the developer to add basic encryption capabilities to his/her projects with minimum effort, and without the need of having deep knowledge on how cryptography works.

Features:

  • Provides easy encryption tools for little adoption effort.
  • Also provides highly configurable standard encryption tools, for power-users.
  • All encryption tools comply with encryption best practices and security recommendations. They are also thread-safe to avoid concurrency problems even in multi-threaded environments like web applications.
  • Jasypt-hibernate provides a transparent mechanism for persisting data in an encrypted form using Hibernate.
  • All encryption tools are designed to be easily integrable into IoC containers like the Spring Framework, although, of course, it can be used without one.

    I haven’t had a chance to play with it yet, but I really like the hibernate library that allows transparent persistence of database fields. Most developers find that work depressingly difficult so security usually suffers but if Jasypt does its job perhaps we’ll get some more security without extra work.

Filed under: — @ 2007-01-30 00:00:00
2007-01-30 00:00:00

Jasypt: Java encryption library that eases encryption of database fields too

If you’re writing healthcare apps in Java, take a look at Jasypt. Especially if you need to encrypt data in your databases. Here’s how the authors describe it:

Jasypt is a java library which allows the developer to add basic encryption capabilities to his/her projects with minimum effort, and without the need of having deep knowledge on how cryptography works.

Features:

  • Provides easy encryption tools for little adoption effort.
  • Also provides highly configurable standard encryption tools, for power-users.
  • All encryption tools comply with encryption best practices and security recommendations. They are also thread-safe to avoid concurrency problems even in multi-threaded environments like web applications.
  • Jasypt-hibernate provides a transparent mechanism for persisting data in an encrypted form using Hibernate.
  • All encryption tools are designed to be easily integrable into IoC containers like the Spring Framework, although, of course, it can be used without one.

    I haven’t had a chance to play with it yet, but I really like the hibernate library that allows transparent persistence of database fields. Most developers find that work depressingly difficult so security usually suffers but if Jasypt does its job perhaps we’ll get some more security without extra work.

Filed under: — @ 2007-01-30 00:00:00
2007-01-28 00:00:00

Nike + iPod a runners best friend

When it comes to exercise, motivation is the name of the game. Personal training has exploded in the recent years along with personal coaching. It would be great if we all could have someone who would give us that boost just when we need it, but that is not a reality for the majority of us.

Nike and Apple have joined together to create a product that doesn’t eliminate the need for a coach or trainer, but definitely helps with the motivation.

Last year Apple released a wireless pedometer to be used with specific Nike shoes. The wireless pedometer has asensor that attaches to the iPod Nano and there is a small chip that is placed under the sock liner in special Nike+ shoes. The chip communicates to iPod wirelessly, providing information on pace and distance traveled.
If you want to know how fast or how far you have been running, just push the center button and a pleasant voice (male or female, your choice) mutes your music and tells you how long you have been running, what your current pace is and your distance, afterwards your music returns. At the end of your run, the voice returns to give you the entire stats of your run including calories.

In my opinion the wireless pedometer is a great product stand alone, but Nike has taken it one step further and created an online community where you can upload your runs, make goals and challenge other runners throughout the world. At the beginning of this year Nike + added a resolution goal to the site which comes with a free text message option. The text message is your personal electronic coach that will keep you informed on your progress or in my case reprimand me when I am not meeting my goals. For those of you with Apple computers, there is a Nike+ goal widget that keeps track of your goals and your current progress.

The Nike+ has changed the way that I run and increased my motivation. Today I was just half way through my run when fatigue started to set in. All I had to do was think about the nasty text messages that I have been getting from Nike about my poor performance and I was back in the saddle.

Filed under: — @ 2007-01-28 00:00:00
2007-01-24 00:00:00

Cough and Cold Medications May Cause Infant Death

January 16, 2007 ? The US Food and Drug Administration (FDA) has warned healthcare professionals regarding the need for caution when administering cough and cold medications to infants younger than 2 years. Clinicians should also ask caregivers about their use of over-the-counter (OTC) combination medications to avoid the risk for overdose from component duplication.

The warning was based on 3 infant deaths for which cough/cold medications were determined by medical examiners to be the underlying cause, according to an alert sent Friday from MedWatch, the FDA’s safety information and adverse event reporting program.

According to an article published by the US Centers for Disease Control and Prevention in last week’s Morbidity and Mortality Weekly Report, the 3 infants ranged in age from 1 to 6 months; all were found dead in their homes. On autopsy, 2 of the infants (patients 1 and 2) had evidence of respiratory infection.

All 3 infants had what appeared to be high levels of pseudoephedrine in postmortem blood samples (range, 4743 - 7100 ng/mL). According to the CDC, these levels are approximately 9 to 14 times the levels resulting from administration of recommended doses to children aged 2 to 12 years. Two of the infants (patients 1 and 3) had received either an OTC or a prescription product, and patient 2 had received both.

Further examination revealed that patients 2 and 3 had detectable blood levels of dextromethorphan and acetaminophen. Although no detectable postmortem levels were found, patients 1 and 2 had been administered prescription medications containing carbinoxamine.

The CDC notes that although OTC sales of pseudoephedrine-containing products have been banned, some pediatric cough and cold medications containing the drug may still be sold behind the counter.

As an alternative to cough and cold medication in infants, use of a rubber suction bulb to clear congestion should be considered; secretions can be softened with saline nose drops or a cool-mist humidifier.

According to the CDC, systematic reviews of controlled trials of OTC cough and cold medications have concluded they are not more effective than placebo for reducing acute cough and other symptoms of upper respiratory tract infection in children younger than 2 years. Moreover, the American College of Chest Physicians released clinical practice guidelines in 2006 advising healthcare professionals to refrain from recommending cough suppressants and other OTC cough medications for young children because of associated morbidity and mortality.

Currently, there are no FDA-approved dosing recommendations for administering OTC cough and cold medications to infants younger than 2 years. OTC labeling advises caregivers to “consult a doctor” for children in this age group; clinicians often extrapolate a dose from guidelines for older children and adults based on the child’s age or weight, assuming that the disease and drug effects are similar.

Healthcare professionals are advised to educate caregivers regarding the importance of administering cough and cold medications only as directed and the risk for potentially fatal overdose associated with ingredient duplication if additional products are given.

Adverse events potentially related to use of cough/cold products in children younger than 2 years should be reported to the FDA’s MedWatch reporting program by phone at 1-800-FDA-1088, by fax at 1-800-FDA-0178, online at http://www.fda.gov/medwatch, or by mail to 5600 Fishers Lane, Rockville, MD 20852-9787.?

Filed under: — @ 2007-01-24 00:00:00
2007-01-23 00:00:00

Improving Patient Communication often leads to improved healthcare

I recently ran across Emmi Solutions (www.emmisolutions.com), which I was fascinated to learn was co-founded by a surgeon and a computer game designer (not exactly a common combo). What I liked about Emmi was that it facilitates physician-patient communication by providing ???prescription-strength??? multimedia programs to help patients understand what to expect before, during, and after a surgical or invasive medical procedure. As most of us who’ve been in this industry for a while intuitively get, the more a patient knows and understands about their care providers, their diagnoses, and their procedures, the better the patient’s overall health is likely to be.

I liked Emmi’s focus on using common-sense tech solutions so I recently invited Mark Achler, their CEO, to talk about the problem his company is solving. He indicated that whether it???s preparing for a procedure, living successfully with a medical device, or helping people manage a chronic disease, the Emmi system is designed to improve quality by helping patients, their families and caregivers take an active role in their care. While it may sound like a marketing slogan, I actually felt that their solutions could help patients directly (instead of like other technology which helps indirectly through use only by physicians or care providers).

Given Mark’s expertise in the field, I asked him the following question: “How is technology improving patient communication, which in turn, improves their overall healthcare?” Here’s what Mark said:

Technology is a vehicle that we use to help solve a problem that is not getting as much attention as it should. Here???s the problem ??? 90 million Americans have low health literacy. That means, that over half the country has trouble reading the directions on their pill bottles, informed consent forms, insurance information, and the majority of the written patient information in pamphlets and on the Web. And it???s well-studied that better-informed patients have shorter hospital stays, use fewer hospital resources, sue their doctors less, and have better outcomes.

So, to answer your question ??? how can technology help? One way is to leverage technology to extend the doctor???s reach. Doctors are crunched for time. They???d like to spend more time helping patients understand their conditions, how to care for themselves, what???s involved with a procedure, etc, but the clock is ticking and the waiting room is full. Patients want and need better, clearer, understandable and actionable information so they can get involved with their treatment.

As patients, we need to work to change what has evolved into an almost ???confrontational??? relationship with the healthcare world, and transform it into a true partnership. The goal is to reach a level of good communication that allows everybody in the patient care equation to share a common language and understanding.

This is where the power of technology comes into play. Today, patients and their families expect more from their physicians. But there are many challenges in properly informing, educating and managing patients??? questions and expectations. Almost everyone agrees that technology can, and should, be used to facilitatethe process. And when correctly implemented, technology, in our case a Web-based platform, can offer the perfect ???vehicle??? to educate patients, manage their expectations and communicate more effectively.

The concept is simple: provide healthcare information to patients which will, in turn, appropriately set expectations and drive behavioral change. In order to do this, the information needs to be accessible and empathetic to be emotionally engaging. And if healthcare professionals can inform patients about what to expect from a procedure in language they can truly understand, it can help build trust, minimize misunderstanding, improve compliance and outcomes, and cut malpractice risks. This new form of communication requires flexible communication tools that can be implemented at every health interaction to document all provider-patient exchanges, and that can take difficult-to-understand information and transform it into a form that everyone can comprehend.

Today, more and more decision makers are interested in e-health tools as critical components of personal health management and healthcare reform strategies. Decision makers are seeking viable approaches to reduce healthcare costs, improve the quality of care, and increase consumers??? ability to manage their own health.

In a field where trust and good communication is critical to quality and safety, Web-based tools should be highly regarded as an intervention that cansimplify complex information, encourage patient involvement and affect behavioral change. After all, better-informed patients who are engaged in their own care establish benefits that cascade across all healthcare organizations and interests.

Filed under: — @ 2007-01-23 00:00:00
2007-01-23 00:00:00

Improving Patient Communication often leads to improved healthcare

I recently ran across Emmi Solutions (www.emmisolutions.com), which I was fascinated to learn was co-founded by a surgeon and a computer game designer (not exactly a common combo). What I liked about Emmi was that it facilitates physician-patient communication by providing ???prescription-strength??? multimedia programs to help patients understand what to expect before, during, and after asurgical or invasive medical procedure. As most of us who’ve been in this industry for a while intuitively get, the more a patient knows and understands about their care providers, their diagnoses, and their procedures, the better the patient’s overall health is likely to be.

I liked Emmi’s focus on using common-sense tech solutions so I recently invited Mark Achler, their CEO, to talk about the problem his company is solving. He indicated that whether it???s preparing for a procedure, living successfully with a medical device, or helping people manage a chronic disease, the Emmi system is designed to improve quality by helping patients, their families and caregivers take an active role in their care. While it may sound like a marketing slogan, I actually felt that their solutions could help patients directly (instead of like other technology which helps indirectly through use only by physicians or care providers).

Given Mark’s expertise in the field, I asked him the following question: “How is technology improving patient communication, which in turn, improves their overall healthcare?” Here’s what Mark said:

Technology is a vehicle that we use to help solve a problem that is not getting as much attention as it should. Here???s the problem ??? 90 million Americans have low health literacy. That means, that over half the country has trouble reading the directions on their pill bottles, informed consent forms, insurance information, and the majority of the written patient information in pamphlets and on the Web. And it???s well-studied that better-informed patients have shorter hospital stays, use fewer hospital resources, sue their doctors less, and have better outcomes.

So, to answer your question ??? how can technology help? One way is to leverage technology to extend the doctor???s reach. Doctors are crunched for time. They???d like to spend more time helping patients understand their conditions, how to care for themselves, what???s involved with a procedure, etc, but the clock is ticking and the waiting room is full. Patients want and need better, clearer, understandable and actionable information so they can get involved with their treatment.

As patients, we need to work to change what has evolved into an almost ???confrontational??? relationship with the healthcare world, and transform it into a true partnership. The goal is to reach a level of good communication that allows everybody in the patient care equation to share a common language and understanding.

This is where the power of technology comes into play. Today, patients and their families expect more from their physicians. But there are many challenges in properly informing, educating and managing patients??? questions and expectations. Almost everyone agrees that technology can, and should, be used to facilitatethe process. And when correctly implemented, technology, in our case a Web-based platform, can offer the perfect ???vehicle??? to educate patients, manage their expectations and communicate more effectively.

The concept is simple: provide healthcare information to patients which will, in turn, appropriately set expectations and drive behavioral change. In order to do this, the information needs to be accessible and empathetic to be emotionally engaging. And if healthcare professionals can inform patients about what to expect from a procedure in language they can truly understand, it can help build trust, minimize misunderstanding, improve compliance and outcomes, and cut malpractice risks. This new form of communication requires flexible communication tools that can be implemented at every health interaction to document all provider-patient exchanges, and that can take difficult-to-understand information and transform it into a form that everyone can comprehend.

Today, more and more decision makers are interested in e-health tools as critical components of personal health management and healthcare reform strategies. Decision makers are seeking viable approaches to reduce healthcare costs, improve the quality of care, and increase consumers??? ability to manage their own health.

In a field where trust and good communication is critical to quality and safety, Web-based tools should be highly regarded as an intervention that can simplify complex information, encourage patient involvement and affect behavioral change. After all, better-informed patients who are engaged in their own care establish benefits that cascade across all healthcare organizations and interests.

Filed under: — @ 2007-01-23 00:00:00
2007-01-22 00:00:00

Adding full-text searching to Relational Databases

Relational databases like ORACLE, SQL*Server, and MySQL are great at storing structured data in rows and columns and managing relationships across tables. Relational database are also more write-friendly than read-friendly (like searching). What that means is that vendors and developers often structure the tables and columns more to make it easy for them to write data into than for users to read data out of (because users are always more creative than we think they are).

One way to get around structural limitations is to put full-text searching ontop of structured data . One such tool, DBSight, is an inexpensive but useful application that allows you to point to any relational database and then do Google- or Amazon-like searches. While I recommend full-text searching because it is a great addition to most relational databases, you need to make sure you design the privacy and security rules appropriately otherwise users might get access to stuff they shouldn’t.

If you haven’t done so already, start asking your vendors to give you full-text searching capabilities in your applications so that they can manage the privacy and security rules.

Filed under: — @ 2007-01-22 00:00:00
2007-01-22 00:00:00

Adding full-text searching to Relational Databases

Relational databases like ORACLE, SQL*Server, and MySQL are great at storing structured data in rows and columns and managing relationships across tables. Relational database are also more write-friendly than read-friendly (like searching). What that means is that vendors and developers often structure the tables and columns more to make it easy for them to write data into than for users to read data out of (because users are always more creative than we think they are).

One way to get around structural limitations is to put full-text searching on top of structured data . One such tool, DBSight, is an inexpensive but useful application that allows you to point to any relational database and then do Google- or Amazon-like searches. While I recommend full-text searching because it is a great addition to most relational databases, you need to make sure you design the privacy and security rules appropriately otherwise users might get access to stuff they shouldn’t.

If you haven’t done so already, start asking your vendors to give you full-text searching capabilities in your applications so that they can manage the privacy and security rules.

Filed under: — @ 2007-01-22 00:00:00
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