Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
A July 2026 narrative review in Diagnosis examined whether artificial intelligence and large language models can reduce diagnostic error in bedside and clinic consultations. It summarized evidence that diagnostic errors affect 5-10% of admissions and visits and contribute to patient harm and hospital mortality.
As of June 10 2025, this peer-reviewed review describes multimodal AI that integrates medical imaging, genomic information, electronic health records, and wearable data across biomaterials science, diagnostics and personalized medicine, citing AlphaFold for protein structure prediction and systems that combine imaging, molecular markers and clinical data
By June 2025, a systematic review in Molecular Cancer surveyed current AI technologies across cancer care, from imaging diagnostics with CT, MRI, PET, ultrasound and digital pathology to genomics, liquid biopsies, and therapeutic tools including decision support, treatment planning, drug discovery, radiation therapy and robotic surgery.
By June 10 2025, this peer-reviewed review in Bioengineering synthesized current implementations of large language models in healthcare, describing their use across clinical decision support, medical education, diagnostics, and patient care, and detailing methods like domain-specific pre-training and supervised fine-tuning.
By July 2026, this systematic review synthesized 141 studies to map seven emerging paradigms beyond generative AI, including Emotional and Empathetic AI, Social AI, Agentic AI, Multimodal AI, Explainable AI, and Responsible AI, documenting a shift from purely technical research to socio-technical integration.
As of its July 2, 2026 publication, this peer-reviewed article analyzes how deepfake and synthetic-media harms are produced through combined conduct of generative-model developers, prompting users, platforms and secondary distributors, and argues ordinary tort doctrine does not easily resolve the resulting civil-liability problem in Saudi and Jordanian law.
By July 2026, researchers had surveyed 69 Japanese university students about everyday GenAI use and analyzed responses with systematic grounded theory. They found students moved through an iterative moral trajectory from recognizing power and risk to feeling ethical anxiety, then to reflexive evaluation and conditional trust, captured in the NECoAI model.
A 2026 position paper examines AI systems that record voice and video during pediatric emergencies, noting they are emerging as HCI technologies with implications for clinical work and are promoted for documentation, team performance, and debriefing. The authors argue that clinicians, parents, and child patients have been largely absent from design and governance.
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