AI Medical Compendium

Novel machine learning-based approach to identify viral biomarkers of human respiratory emissions from oral and nasal metagenomes.

mSphere Apr 13, 2026

Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental sampling of respiratory viral pathogens is often challenging because of frequent non-detect measurements... read more

Toward AI-Powered Cancer Etiology Research.

Cancer discovery Apr 13, 2026

Advances in multimodal longitudinal data and artificial intelligence (AI) create new opportunities for cancer etiology research. We envision an AI-powered discovery workflow integrating an interoperable epidemiologic data ecosystem and causal inferen... read more

Training the Next Generation of AI-Enabled Cancer Scientists.

Cancer discovery Apr 13, 2026

Despite unprecedented opportunities at the convergence of artificial intelligence (AI) and cancer research, few scientists possess fluency in both domains. We propose a six-principle framework for training "AI-oncology bilingual" scientists who can b... read more

Inferring rheumatoid arthritis disease activity status from the electronic health records across health systems.

Arthritis & rheumatology (Hoboken, N.J.) Apr 13, 2026

OBJECTIVE: Disease activity plays a central role in rheumatoid arthritis (RA) clinical studies. The inconsistent availability of data on disease activity in real-world electronic health records (EHR) data has limited the ability to generate real-worl... read more

Accuracy of Large Language Models in Frequently Answering Questions Related to Presurgical Nasoalveolar Molding.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association Apr 13, 2026

ObjectiveTo assess the accuracy, readability, and comparative quality of five large language models (LLMs) in answering frequently asked questions related to nasoalveolar molding (NAM) in cleft care.DesignRepeated measures study.SettingThis study eva... read more

Running an electron microscopy core facility.

Journal of microscopy Apr 13, 2026

As electron microscopes became more costly, technically complex, and integral to a wide range of scientific fields, centralised electron microscopy (EM) core facilities have become essential for maintaining accessibility, performance, and quality. Dr... read more

AI-based evaluation of implant abutment screw torque decay: A periapical radiograph pilot study.

Journal of periodontology Apr 13, 2026

BACKGROUND: To develop a deep learning framework for non-invasive detection of implant abutment central screw torque decay using periapical radiographs, addressing the clinical challenge of mechanical screw loosening without invasive intervention. ME... read more

Beyond autonomy: why medicine needs artificial intelligence teammates, not artificial intelligence doctors.

Diagnostic and interventional radiology (Ankara, Turkey) Apr 13, 2026

Unsupervised phenotyping of the periodontal architecture through high-dimensional clustering of electronic health records: A multicenter study.

Journal of periodontology Apr 13, 2026

BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characterizing disease patterns based on the "periodontal architecture" of localized structural failures (toot... read more

Ability of Deep Learning Image Reconstruction to Preserve Detail and Remove Noise in Coronary Computed Tomography Angiography: A Clinical Analysis.

Journal of computer assisted tomography Apr 13, 2026

PURPOSE: To analyze image quality over 3 levels (low, medium, and high) of deep learning image reconstruction (DLIR), evaluate whether edge detail is lost with higher denoising levels. MATERIALS AND METHODS: Nineteen subjects scanned with the institu... read more

Artificial Intelligence Medical Compendium