+ 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 Problems surrounding AI

Documented harms, ranked by source quality, corroboration, and recency. Reader feedback is shown separately and never changes the evidence rank. 201 records · page 1 of 7.

201 results
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01
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedHealth

Development of computational pathology foundation models is constrained by limited data accessibility, high variability across datasets, need for domain-specific adaptation, and lack of standardized evaluation benchmarks

Source article: A survey on computational pathology foundation models: datasets, adaptation strategies, and evaluation tasks

Knowledge and Information Systems · npj Digital Medicine
02
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewed ×2Sports

Rapid adoption of AI in sports raises complex legal challenges involving data protection, intellectual property, liability, and ethics that current frameworks may not adequately address.

Source article: Legal Foundations for the Application OF Artificial Intelligence Technologies in the Sports Industry

Neliti · International Journal of Human–Computer Interaction
06
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedPolicy

AI deepfake tools enable unauthorized manipulation and dissemination of individuals' images, voices and behaviours without consent, exposing them to digital exploitation.

Source article: AI-Generated Likeness and The Law: Protecting Personality Rights in The Age of Deepfakes and Social Media Exploitation

Economic Sciences · The Eurasia Proceedings of Science Technology Engineering and Mathematics
09
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedPolicy

In low- and middle-income countries, AI for healthcare faces systemic barriers including contextual bias from non-representative datasets and low governance and workforce readiness.

Source article: Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings—a scoping review

Frontiers in Digital Health · Pathfinder of Research
10
Reader signal

How should this claim be treated?

11
Reader signal

How should this claim be treated?

13
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedMedia & Arts

Users of AI art platforms showed limited awareness of structural issues, as cultural bias in training data and algorithmic transparency were rated lower in importance than autonomy and usability.

Source article: Generative AI Art and Creative Subjectivity: A Mixed-Methods Study Based on Grounded Theory and CRITIC

Asia-pacific Journal of Convergent Research Interchange
14
Reader signal

How should this claim be treated?

16
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedHealth

Large language models (LLMs) may help organize clinical information, but their use in perioperative settings requires careful evaluation because errors may have immediate safety implications.

Source article: A large language models-assisted and expert-corrected workflow for preoperative anesthesia assessment drafts: A single-centre exploratory feasibility study

Medicina Clínica
17
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedHealth

Systematic assessment of the medical utility of radiology and diagnostic Artificial Intelligence in fracture detection (SAMURAI-fracture): a protocol for a multicentre cluster-randomised controlled trial: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs.

Source article: Systematic assessment of the medical utility of radiology and diagnostic Artificial Intelligence in fracture detection (SAMURAI-fracture): a protocol for a multicentre cluster-randomised controlled trial

BMJ Open
21
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedScience

The optimized ANN and Logistic Regression frameworks exhibited the highest overall discriminative power (AUC > 0.99), while the Random Forest algorithm achieved the peak classification accuracy (97.10%).

Source article: Evaluating machine learning and neural network architectures for forensic sex estimation using mandibular ramus and notch features on panoramic radiographs

International Journal of Legal Medicine
22
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedHealth

Most artificial intelligence (AI) models used in radiology are black boxes-they produce predictions without explaining the basis of their outputs, raising concerns about clinical safety, accountability, and trust.

Source article: Explainable artificial intelligence in medical imaging: how to interpret, evaluate, and use artificial intelligence explanations

Diagnostic and Interventional Radiology
23
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedHealth

EXPRESS: Relation between Albumin-Corrected Anion Gap and In-Hospital Mortality in Patients with Traumatic Lung Injury: A Multicenter Retrospective Cohort Study and the Development of Machine Learning-Based Prediction Models: Elevated ACAG was substantially linked to a high risk of mortality in individuals with TLI (hazard ratio (HR) [95% confidence interval (CI)] = 1.115 [1.037-1.199]).

Source article: EXPRESS: Relation between Albumin-Corrected Anion Gap and In-Hospital Mortality in Patients with Traumatic Lung Injury: A Multicenter Retrospective Cohort Study and the Development of Machine Learning-Based Prediction Models

Journal of Investigative Medicine
28
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedEducation

AI has been rapidly integrated into educational settings without a profound and critical evaluation of its assumptions and consequences for knowledge and power in leadership.

Source article: AI Challenges and the Future of Education: A Needed Epistemic, Political, and Ecological Agenda for Critical Leadership Scholars and Practitioners

New Directions for Student Leadership
29
Reader signal

How should this claim be treated?

Evidence-backed problemPeer-reviewedHealth

AI facial image scoring, editing and curation systems converge on a narrow westernized phenotype and are linked to appearance dissatisfaction, perception drift, and Snapchat and Zoom dysmorphia presentations in plastic surgery patients.

Source article: Artificial Intelligence in Plastic Surgery of the Face: Implications for Esthetic Standards, Patient Perception, and Clinical Practice

Journal of Craniofacial Surgery