+ HEALTH Aims Intramuscular fat (IMF) is increasingly recognized as a marker of ectopic adiposity and adverse cardiome…+ HEALTH Periapical lesions are challenging to detect on intraoral radiographs because of anatomical superimposition a…± HEALTH Ultrasound imaging is an indispensable diagnostic tool, yet its profound reliance on operator expertise inher…+ HEALTH Objectives We adapted the individualized polysocial risk score (iPsRS), a machine learning model originally d…± HEALTH Melioidosis is a life-threatening infectious disease caused by Burkholderia pseudomallei ( Bp ). Rapid diagno…+ HEALTH Classification is a core machine learning task, and ensemble voting methods are widely used to improve predic…+ CLIMATE Microplastic (MP) pollution poses escalating environmental risks, demanding efficient and reproducible tools…± HEALTH Medicinal chemistry sits at the center of modern drug discovery, yet translating molecular designs into appro…
TruaceTracing the truth around AIWednesday, August 26, 2026
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The Index

What the evidence says.What the public feels.

Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.

1,155 results
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AI gains · 641

78
GainHealth· Newly added· Evidence: Moderate (1 source)

A model combining clinical and sociodemographic variables predicted overall survival in cervical squamous cell carcinoma with acceptable discrimination.

Researchers conducted a population-based retrospective analysis of 5392 patients with cervical squamous cell carcinoma in the SEER database from 2004 to 2015, using multivariable logistic regression and machine learning to evaluate sociodemographic and clinical predictors of overall survival. They found marital status, median household income, tumor grade, disease stage and tumor size were collectively related to prognosis, and built a model including age and race that achieved an AUC of 0.70.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%99

Updated Aug 24, 2026 · TRV-2026-0860

78
GainEducation· Newly added· Evidence: Moderate (1 source)

ChatGPT can support teaching and learning by enabling personalized interactive instruction and creating formative assessment prompts that give ongoing feedback.

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.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%99

Updated Aug 19, 2026 · TRV-2026-0835

78
GainHealth· Newly added· Evidence: Moderate (1 source)

Meta-analysis of 19 studies with 100,790 participants found AI/ML models achieved pooled discrimination of 0.836 for predicting tuberculosis treatment failure.

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.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%98

Updated Aug 18, 2026 · TRV-2026-0817

AI problems · 514

78
ProblemHealth· Stable· Evidence: Moderate (1 source)

AI-driven modeling for antimicrobial resistance target discovery continues to face persistent challenges around experimental validation and genomic variability, limiting confirmation of predicted functions.

By July 30 2026, a narrative review in Journal of Computer-Aided Molecular Design described the use of structural modeling and artificial intelligence for functional prediction of proteins encoded by multidrug-resistant bacterial genomes. It reported that tools such as AlphaFold and RoseTTAFold have enabled high-accuracy three-dimensional structure prediction, facilitating annotation of hypothetical proteins and identification of conserved domains and catalytic sites.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%95

Updated Jul 31, 2026 · TRV-2026-0599

78
ProblemClimate· Stable· Evidence: Moderate (1 source)

The same gradient-boosted models showed poor agreement with observed MICs for ampicillin and piperacillin-tazobactam and struggled with beta-lactamase inhibitor combinations.

A One-Health study analyzed 30,554 E. coli whole-genome sequences from human, animal and environmental sources across 126 countries from 2000 to 2025, using AMRFinderPlus and MLST to map resistance genes and clones, and applied gradient-boosted machine learning to predict MICs from gene profiles and chromosomal features.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%94

Updated Jul 29, 2026 · TRV-2026-0584

78
ProblemEducation· Stable· Evidence: Moderate (1 source)

University policy frameworks still lack comprehensive coverage of data privacy protections and equitable access to GAI tools.

Published December 19, 2024, this peer-reviewed study analyzed generative AI adoption policies and guidelines from 40 universities across six global regions through the lens of Diffusion of Innovations Theory. It examined how institutions frame compatibility, trialability, observability, communication channels, and roles and responsibilities.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%93

Updated Jul 24, 2026 · TRV-2026-0549

78
ProblemEducation· Stable· Evidence: Moderate (1 source)

Students expressed concerns that ChatGPT promotes cheating and plagiarism and is less reliable for classroom learning and less useful for developing critical thinking, interpersonal communication, and decision-making skills.

In early 2024, researchers surveyed 23,218 higher education students in 109 countries and territories about ChatGPT. Students reported using it mainly for brainstorming, summarizing texts, and finding research articles, finding it helpful for simplifying complex information but less reliable for providing information and supporting classroom learning.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%93

Updated Jul 24, 2026 · TRV-2026-0541

Recomputed live from the record · Aug 26, 2026, 11:45 PM