AI Medical Compendium Journal:
Communications medicine

Showing 1 to 7 of 7 articles

HIV-1 suppression and rare dolutegravir resistance in antiretroviral-experienced people with HIV in Liberia.

Communications medicine
BACKGROUND: Increasingly, persons with HIV in Liberia are receiving antiretroviral therapy containing the integrase strand-transfer inhibitor (InSTI) dolutegravir (DTG), but the prevalence of and factors associated with virologic failure and HIV drug...

Comprehensive testing of large language models for extraction of structured data in pathology.

Communications medicine
BACKGROUND: Pathology departments generate large volumes of unstructured data as free-text diagnostic reports. Converting these reports into structured formats for analytics or artificial intelligence projects requires substantial manual effort by sp...

Development and multicenter validation of chest X-ray radiography interpretations based on natural language processing.

Communications medicine
BACKGROUND: Artificial intelligence can assist in interpreting chest X-ray radiography (CXR) data, but large datasets require efficient image annotation. The purpose of this study is to extract CXR labels from diagnostic reports based on natural lang...

Improving personalized tumor growth predictions using a Bayesian combination of mechanistic modeling and machine learning.

Communications medicine
BACKGROUND: In clinical practice, a plethora of medical examinations are conducted to assess the state of a patient's pathology producing a variety of clinical data. However, investigation of these data faces two major challenges. Firstly, we lack th...

A BERT model generates diagnostically relevant semantic embeddings from pathology synopses with active learning.

Communications medicine
BACKGROUND: Pathology synopses consist of semi-structured or unstructured text summarizing visual information by observing human tissue. Experts write and interpret these synopses with high domain-specific knowledge to extract tissue semantics and fo...

How will artificial intelligence change medical training?

Communications medicine
Artificial intelligence is changing medicine and it will relieve physicians from the burden of rote knowledge. Here, I discuss how this might affect medical training, drawing from the example of how automation in aviation redefined the role of the pi...

Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading.

Communications medicine
BACKGROUND: Gleason grading of prostate cancer is an important prognostic factor, but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial intelligence (A.I.) tools have demonstrated Gleason gradin...