mediKanren VS dissertation-single-spaced

Not really production, but probably THE most impressive biomedicine research work I've seen (and I'm an academic MD):

https://github.com/webyrd/mediKanren

This is a FOL theorem prover that uses medical research articles as terms. They use it to do genetics and drug repurposing metaresearch. It's like the wet dream of all the biomed machine learning fanboys out there, except that:

1. it's not machine learning

and

2. it really works

And wow, he uses logic programming to deduce a diagnostic from the facts https://github.com/webyrd/mediKanren .. and used to find out what his son had https://www.statnews.com/2019/07/25/ai-expert-writing-code-save-son/

Hi Kamaal!

I know Cisco is using core.logic, which is David Nolen's Clojure variant of miniKanren, in their ThreatGrid product. I think the Enterprisey uses of mediKanren are a bit different than the purely relational programming that I find most interesting, though.

Having said that, we are now on our second generation of mediKanren, which is software that performs reasoning over large biomedical knowledge graphs:

https://github.com/webyrd/mediKanren/tree/master/medikanren2

mediKanren is being developed by the Hugh Kaul Precision Medicine Institute at the University of Alabama at Birmingham (HKPMI). HKPMI is run by Matt Might, who you may know from his work on abstract interpretation and parsing with derivatives, or from his more recent work on precision medicine. mediKanren is part of the NIH NCATS Biomedical Data Translator Project, and is funded by NCATS:

https://ncats.nih.gov/translator

Greg Rosenblatt, who sped up Barliman's relational interpreter many order of magnitude, has been hacking on dbKanren, which augments miniKanren with automatic goal reordering, stratified queries/aggregation, a graph database engine, and many other goodies. dbKanren is the heart of mediKanren 2.

I can imagine co-writing a book on mediKanren 2, and its uses for precision medicine...

Cheers,

--Will

The Precision Medicine Institute that I now run produces mediKanren: https://github.com/webyrd/mediKanren

It's an open source logical reasoning engine (read: 1960's AI) for drug repurposing that we deploy routinely to help patients.

There is always a need for better relationalization of biological data sets that feed such tools too.

For example, SemMedDB is really showing its age for NLP of the scientific literature and yet it is still astonishingly useful for helping patients even as is.

> In general, my opinion is that Prolog's approach is pragmatic, but it was designed in the 1970's when hardware was weaker. With modern hardware, there may be different options that better address the need for purity without sacrificing efficiency.

I agree. We are investigating various approaches to improve the efficiency of the search, while retaining completeness, for example.

> Regarding incompleteness, some modern Prologs use SLG-resolution (a.k.a. tabling) to at least avoid the incompleteness resulting by infinite left-recursions. This still allows infinite right recursions but it's easy to get in such a situation with recursion, or even just iteration, in any Turing complete language. I feel that tabling goes a long way towards addressing incompleteness.

I agree that tabling is useful. Tabling is useful even with a complete search, since it can cut off certain cases in which there are infinitely many answers of similar form, and can change the complexity class of queries.

A section of my dissertation discusses adding tabling to miniKanren, based on code Ramana Kumar and I worked on, after discussions and readings with Dan Friedman:

https://github.com/webyrd/dissertation-single-spaced

That tabling implementation is very tricky, though, and doesn't support constraints other than unification. It's time to revisit and update tabling in miniKanren, I think.

> Modern Prolog interpreters generally have an option to enable the occurs check (for example, in Swi-Prolog there's an environment flag to enable it for all unifications) and there's also the ISO predicate unify_with_occurs_check/2, that can be used in meta-interpreters, I guess. I think this addresses the soundness concern.