Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Published December 7, 2023, this exploratory synthesis examines ChatGPT after its November 30, 2022 public release and rapid adoption, reviewing recent literature on how the tool is being used in education. It identifies potential benefits for personalized and interactive learning and for formative assessment, while also noting drawbacks.
By August 2026, a systematic review and meta-analysis of 34 studies evaluated AI and machine learning models to predict tuberculosis treatment failure. Nineteen studies with 100,790 participants were pooled, yielding an AUC of 0.836 with high heterogeneity, with tree-based and multimodal approaches common and most publications appearing after 2019.
Published August 13, 2026 as a peer-reviewed review in Frontiers in Cardiovascular Medicine, the article synthesizes recent advances using machine learning together with multi-omics to address cardiovascular disease heterogeneity where conventional one-size-fits-all strategies often yield limited benefit.
On 2026-08-13, a peer-reviewed article reported a European-wide survey to set regulatory science research priorities for AI use in the medicine lifecycle. Authors developed 28 research questions across seven domains and collected 273 responses from regulators, industry, patients and consumers, academics, and healthcare professionals, finding convergence in rankings across groups.
Between January 2024 and January 2026, a health district in Australia implemented a digital wound model of care combining an AI-enabled app with a virtual command centre across four hospitals and five community health centres. A post-implementation evaluation surveyed and interviewed 94 patients, 75 frontline clinicians, 9 senior wound nurses and a product manager, reviewing governance minutes to assess acceptability and perceived benefit.
A PRISMA-guided systematic review of 35 studies examined classical AI for treatment optimization in adult bipolar disorder across five outcomes: acute response, long-term maintenance, relapse/readmission, safety/dose, and brain aging/phenotyping. By the July 2026 publication date, pooled performance ranged from modest for acute response (AUC 0.68) to moderate-to-high for maintenance (AUC 0.80) and high accuracy for safety/dose (85%-97%).
Published September 23 2025 as a peer-reviewed review, the article surveys how AI is being applied across healthcare, from analyzing electronic health records and medical imaging to supporting drug discovery, predictive analytics, telemedicine and wearable biosensors, with emphasis on low-resource and remote settings.
On 2025-11-05, Applied Sciences published a comprehensive review of machine learning for financial fraud detection. The authors surveyed supervised, unsupervised and hybrid approaches across credit card, financial statement, insurance and money laundering fraud, reviewed datasets and metrics, and included two case studies applying supervised models to real-world banking data.
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