Zero Knowledge Discovery Laboratory @zedlab_
Covering the latest machine learning news and research from the ZED Lab @UKY. Led by Professor Ishanu Chattopadhyay @ishanu_ch zed.createuky.net Lexington, KY Joined August 2018-
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Speaking at Wake Forest Center for AI linkedin.com/posts/wakefore…
Excited to speak at the Pritzker Forum on @_GlobalCities on deploying AI for Safer Communities globalaffairs.org/pritzker-forum… @AgustiFdeLosada @SaferFoundation @MultitudeLEA @CaptHosein
My commentary on impact of social determinants of health to identify US Veterans at risk of self-harm out in JAMA. I talk about the implications, limitations of emerging machine learning tools in diagnosing suicidal ideation or future attempts. jamanetwork.com/journals/jaman…
Our new paper in Nature Medicine on universal predictive screening of a rare/often fatal disease (IPF) demonstrates the need for Bio-AI, off-the shelf AI tools might not be robust enough for clinical applications.
(4/4) ZCoR-IPF results indicate that past respiratory disorders maximally contribute to IPF risk, followed by known comorbidities, metabolic, cardiovascular & dis of the eye, infections. Risk remains substantially invariant across the sexes. nature.com/articles/s4159…
(1/4) Our paper on universal screening for Idiopathic Pulmonary Fibrosis (IPF) is out in Nature Medicine. nature.com/articles/s4159… Reliable prediction upto 4yrs before diagnosis by current practice. ~3M patients & 3 patient databases. Collab with Weill Cornell, Harvard, Mayo Cl
(3/4) The predictive tool ZCoR-IPF was trained on Marketscan, UChicago Med, Mayo Clinic data, with 2,983,215 participants, & 54,247 positive cases. Achieved positive likelihood ratios greater than 30 at a specificity of 0.99 across different cohorts. nature.com/articles/s4159…
(2/4) Uncovered predictive comorbidity signatures in past 2 years of individual history of medical encounters to reliably flag patients who get diagnosed with for IPF in future. Demonstrate the crucial role machine learning/AI can play in diagnosis of rare diseases.
This is work in collaboration with Dmytro Onishchenko, Daniel Rubin @danielrubinmd , and R. Parker Ward of the University of Chicago Medicine @UChicagoMed @ScienceLife and James R. Horne of Southern Oregon Orthopedics, Medford, OR
We analyze patient data already in file, with no new lab tests, to assess the risk of a major cardiac event after elective hip/knee replacement surgery. Beats existing state of the art risk measures.
Our new paper out in the Journal of American Heart Association. "Cardiac Comorbidity Risk Score: Zero‐Burden Machine Learning to Improve Prediction of Postoperative Major Adverse Cardiac Events in Hip and Knee Arthroplasty"ahajournals.org/doi/full/10.11…
Markov chains & processes were invented to show that dependencies between outcomes could still obey the central limit theorem, countering Nekrasov’s argument that because Russian crime reports obeyed the law of large numbers, crime reflected acts of free will.
For math & stats nerds, amazing how many innovations have emerged from critical studies of criminal justice--Poisson's distribution was discovered analyzing the number of wrongful convictions in a country;
Our precise predictions (90% accuracy for property and violent crimes predicted 7 days in advance within ~1,000 ft) are based on a novel machine learning model inspired by the depth of neural networks but with a very different underlying architecture tuned to events in time.
The study from @NatureHumBehav uses publicly available data on violent and property crimes, and was validated on 8 different US cities nature.com/articles/s4156…
@TomCruise bro, they totally stole your idea. nature.com/articles/s4156…
A new algorithm can predict crime in US cities a week before it happens trib.al/ix6pSnx
Algorithm predicts crime a week in advance, but reveals bias in police response nature.com/articles/s4156… #science #social_science #algorithm #crime #week #advance
New article for precise event-level crime prediction is now out in Nature Human Behavior (nature.com/articles/s4156…)
Deep-learning model may accurately predict autism diagnosis spectrumnews.org/news/deep-lear… via @Spectrum
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