A machine learning tool for early identification of celiac disease autoimmunity.

Identifying which patients should undergo serologic screening for celiac disease (CD) may help diagnose patients who otherwise often experience diagnostic delays or remain undiagnosed. Using anonymized outpatient data from the electronic medical records of Maccabi Healthcare Services, we developed and evaluated five machine learning models to classify patients as at-risk for CD autoimmunity prior to first documented diagnosis or positive serum tissue transglutaminase (tTG-IgA). A train set of highly seropositive (tTG-IgA > 10X ULN) cases (n = 677) with likely CD and controls (n = 176,293) with no evidence of CD autoimmunity was used for model development.

Evaluation of a machine learning tool for the early identification of patients with undiagnosed psoriatic arthritis - A retrospective population-based study.

Background: Psoriatic arthritis (PsA), an immune-mediated chronic inflammatory skin and joint disease, affects approximately 0.27% of the adult population, and 20% of patients with psoriasis. Up to 10% of psoriasis patients are estimated for having undiagnosed PsA.

Efficiently finding information on the Internet.

The Internet: a vast frontier of endless information. Despite this gold mine of knowledge, most users remain lost in cyberspace with little knowledge of what is available, where or how to find these treasures. Popular communities such as America Online have emerged because they help to organize the content into manageable pieces.

Fetal CNS transplants into adult spinal cord: techniques, initial effects, and caveats.

Transplantation of 11 day gestation rat fetal cortex and spinal cord into adult rat thoracic spinal cord is feasible. However, the techniques used at present for the implantation of the fetal transplant result in host spinal gray matter necrosis. One day after implantation the transplant is in a fluid-filled cyst in the host.