Bell Eapen MD, PhD.

Neural networks (NN) are everywhere, from image analytics to NLP to clinical decision support systems. Embeddings are a popular class of techniques that emerged out of NN with diverse applications. embedding is a low-dimensional translation of high dimensional space. For clinicians, embedding is nothing but a simple representation of complex data.

Embeddings are typically used in text analytics and NLP. However, the same concept can be extended to other domains. Take our typing pattern on a keyboard, for example. It is potentially a complex pattern that involves speed, the sequence of keys and the lag between keys. Typingdna finds an innovative way of converting this complex pattern into an embedding. The obvious use case is to use that embedding to identify the user and use it as a supplementary authentication mechanism. Typingdna provides a Javascript library that you can embed on any webpage and capture the typing embedding from any textbox! typingdna also provides a backend API for comparing the embedding for similarity.

Typing is a complex activity that requires interaction between the nervous system and the musculoskeletal system. I presume that any change in the neurocognitive state or muscle weakness could impact the typing pattern. Monitoring the changes in the typing embeddings may have applications in the monitoring or diagnosis of these disorders. To cut a long story short, I recently participated in a Devpost hackathon organized by typingdna. I submitted a simple solution that records the typing pattern and graphs the changes and proposed it as a monitoring application for Dermatomyositis. Details of the submission are available here and the simple prototype is here.

On a different note, I recently discovered that TensorflowJS has an inbuilt facemesh model that can detect facial landmarks from webcam streams, all within the browser! I have created a React component called skinmesh, that can harvest facial landmark coordinates (facial embedding) from a webcam or any facial image. I feel this has potential applications in cosmetic dermatology. I have blogged about this here. Give me a shout, if anybody wants to collaborate on creating a suitable backend.

Standardized data collection forms are vital for health information systems. This is particularly true in public health, where there is a host of data collection forms shared by various organizations. InterRAI is a typical example. Standardization is important for collaborative data analytics at various levels, a need that became painfully apparent during the recent COVID-19 pandemic.

Though standardization of content is widely addressed, the standardization of the form appearance and rendering is less so. Many healthcare teams find their information systems incapable of dealing with this requirement. They have to often resort to expensive resources to create these forms using various technologies such as javascript. It is not easy to share such electronic forms (E-Forms) with other organizations because of the different requirements of the host systems.

The HL7 FHIR Questionnaire is emerging as a standard that is capable of dealing with both the content and presentation of E-forms. We proposed the FHIRForm framework to use this standard for form management and introduced an open-source stack for form management. One of the components of the framework is an npm module (javascript) to convert the FHIR Questionnaire resource to a JSON schema that can be used by popular form rendering libraries can use. The component called FHIRFormJS can also convert the form submission into a QuestionnaireResponse resource that can be submitted to any FHIR compliant servers. Below is a sample ReactJS application that uses FHIRFormJS to render FHIR Questionnaire.

FHIRFormJS was a work in progress for a long time and was not really stable enough to use. I am excited to introduce the new version of FHIRFormJS that is better and easier made possible by the @ahryman40k/ts-fhir-types library. If you have been using older systems such as LHC-Forms, give FHIRFormJS a try and let me know how we can improve it. Pull requests are most welcome and I have added this repository as a hacktoberfest participant. There is also a sample react application that uses FHIRFormJS (repository link above). If you are using Vue, I have a separate library that targets one of the popular form rendering engines for Vue.

Let me know if you find this interesting and use the GitHub issues for feature requests.

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Counting conditional occurrences using Prolog.

I wanted to implement the following rule in prolog for my IISA project.

If the percentage of coil region is greater than 20% the homologue detection algorithms may become unreliable. The coil module of IISA returns prolog database in the following format.

coil(105,a,0.000).
coil(109,g,0.001).
coil(110,l,0.004).
coil(111,l,0.014).
coil(112,v,0.055).
coil(113,g,0.055).
coil(114,s,0.371).
coil(115,e,0.416).
coil(116,k,0.860).
coil(117,v,0.955).
coil(118,t,0.998).
coil(119,m,0.999).
coil(120,q,0.999).
coil(121,n,0.999).

ie coil(position, aminoacid, probability of being part of coil).

I wanted to count the number of facts with the probability exceeding a cutoff value, say 0.7.

Though it is simple problem, I could not find any solution for this even after googling for few hours. Finally I found this code on the net.

%Code to count the number of proofs for a goal. Found on the net.
count_proof(Goal, N) :-
            flag(counter, Outer, 0),
            (   call(Goal),
                flag(counter, Inner, Inner+1),
                fail;
                flag(counter, Count, Outer),
                N = Count
            ).
Though it worked well (I have still not figured out how!) the code is SWI-Prolog specific and did not work in JLog prolog applet I use for IISA web interface.

Finally I learned about findall and bagof
But still it took some time to figure out how to use findall for my purpose because the description read findall (Var, Database, Array) and to use length(Array). Using coil (_,_,A) as database will count only the number of aminoacids and I didn’t know how to implement the condition A>0.7.
Finally somewhere I found the actual definition for findall (Var, Goal, Array) which solved my problem, though I wasted a whole day on this simple problem.

Here is the final code.

%The region is coil if the value is greater than threshold
coil_region(Cutoff, Val):-
                     coil(_,_,Val),
                     Val>Cutoff.
                    
coil_percent(Region, Total, Percent):-
                     setting(coil,X),
                     findall(Val,coil_region(X,Val),R),
                     length(R,Region),
                     findall(C,coil(_,_,C),A),
                     length(A,Total),
                     Total>0,        %Avoid division by zero
                     Percent is (Region/Total) * 100,!.

coil_percent(0,0,0).

IISA Home Page.

Merck recently gained approval for a vaccine called Zostavax for preventing herpes zoster reactivation in elderly people. This live virus vaccine is unusual in that it is to prevent reemergence, not to prevent initial infection. Can the same concept be used for recurrent herpes simplex infection which is much more disabling than herpes zoster in younger people?

Clinical trials, particularly randomized trials are critical in delivering reliable evidence about the efficacy of an intervention. Clinical trial data can also provide important information about the potential adverse effects of treatment. Currently, not all trials on human participants are reported in the peer-reviewed literature. PLoS Clinical Trials aims to fill this gap. As an open-access journal, all articles published in the journal will be immediately and freely available online. Join them in supporting these goals, and get your paper read by the widest possible audience: submit your trial results today.
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Good Clinical Practice (GCP) guidelines

GCP has two important goals: protection of the subject, and protection of the data which is possible only through adequate training of all concerned staff. An independent audit is needed to ensure compliance to the standards. US FDA acts as enforcement officers. As they are less flexible unconventional approaches have no scope. European agencies are more flexible but they need to be convinced.

The Declaration of Helsinki issued by world medical association insists that all research subjects must be fully informed about the nature and risks of a clinical trial. Protocol design is a responsibility of the investigator and need to be assessed by the concerned ethical committee. The principal investigator has an overall responsibility over the entire project.

Informed consent which includes signing a consent form and a recruiting interview preferably by the physician is extremely important. Though not absolutely necessary it is a good practice to define and describe in writing how all aspects of clinical research are to be conducted. These standard operating procedures (SOPs) must be followed during the execution of the research.