Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Using longitudinal data from 5492 older Chinese adults with chronic conditions in CHARLS, researchers identified three depressive symptom trajectories and compared 10 machine learning models, selecting 10 core predictors via bootstrap RFE and evaluating with stratified split and SHAP interpretability.
Researchers analyzed 473 patients with aneurysmal subarachnoid hemorrhage from the retrospective PROSAH-MPC cohort to test whether admission D-dimer levels and total bleeding volume together predict long-term function. They stratified patients by D-dimer quartiles, ran multivariable logistic regression for 12-month modified Rankin Scale outcomes, selected features with Boruta, and built seven machine learning models interpreted with SHAP.
Researchers developed a CECT-based 2PI system that scores imaging features associated with pathological markers and combined it with clinical parameters in machine learning models to predict postoperative recurrence in solitary HCC 5 cm. In 496 patients across primary and external centers, a threshold of stratified high- versus low-risk groups.
A November 2023 peer-reviewed study surveyed Generation Z students and Generation X and Generation Y teachers about generative AI in higher education. Gen Z respondents were generally optimistic about benefits such as productivity and personalized learning and said they intended to use the tools for educational purposes, while Gen X and Gen Y teachers acknowledged benefits but reported stronger concerns about overreliance and ethical and pedagogical implications.
In a prospective randomized crossover study at Carl R. Darnall Army Medical Center, 21 certified physician assistants interpreted 50 de-identified 12-lead ECGs with and without Queen of Hearts AI software by PMcardio. Diagnostic accuracy rose from 79.0% to 92.9% with AI, with sensitivity 95.4% versus 82.5% and specificity 90.5% versus 75.6%, and interrater agreement improved from kappa 0.58 to 0.86.
Published 4 August 2026 in Internal Medicine Journal, this peer-reviewed perspective examines rural mental health inequity in Australia and argues AI could help with earlier identification of distress and safer, more timely triage when used with telehealth and clinical decision support.
Published August 4 2026 in WORK, this peer-reviewed analysis examines AI integration into labour markets, migration governance and social protection systems. It argues AI functions as institutional infrastructure and shows how continuous classification, automated risk assessment and worker scoring can amplify structural inequalities when deployed at scale.
This scoping review mapped evidence published up to March 2026 on AI in healthcare in Sub-Saharan Africa, focusing on marginalised populations. Searching four databases and grey literature, the authors included 23 sources and synthesised them thematically.
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