patient
PulseAugur coverage of patient — every cluster mentioning patient across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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AssemblyAI expands ambient AI scribes beyond healthcare to vet and legal fields
AssemblyAI is exploring the application of its ambient AI scribe technology beyond healthcare, specifically for veterinary and legal practices. The core technology involves passively capturing professional conversations…
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Ambient AI improves healthcare practitioner well-being, cuts note-taking time
A recent trial demonstrated that ambient AI significantly improved practitioner well-being in healthcare settings. The AI technology reduced work-related exhaustion by 0.44 points and decreased time spent on notes by 0.…
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Brain Implant Enables Disabled Patient to Speak in Real-Time
A brain implant has enabled a disabled patient to communicate in real-time, marking a significant advancement in assistive technology. This breakthrough allows individuals with severe communication impairments to expres…
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Researcher explores AI applications for cancer patient treatment
A researcher is exploring the application of artificial intelligence in cancer patient treatment. This work aims to leverage AI technologies to improve therapeutic outcomes for individuals battling cancer.
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AI assists in first-ever sight-saving brain surgery
A patient has successfully undergone brain surgery with the aid of an AI system designed to protect their vision. This marks the initial clinical use of this AI-guided surgical technique, aiming to preserve sight during…
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AI assists in first live sight-saving brain surgery
A patient has undergone the first live AI-assisted brain surgery aimed at saving their sight. This groundbreaking procedure highlights the potential benefits of artificial intelligence in healthcare, offering care that …
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CareCloud confirms 3.7M patient records stolen in major data breach
CareCloud has confirmed a significant data breach affecting 3.7 million patients. The cyberattack resulted in the theft of sensitive medical records, marking one of the largest healthcare data breaches reported in the U…
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Research paper flags preformulation gap in LLM medical consultation evaluations
A new research paper highlights a significant gap in how large language models (LLMs) are evaluated for medical consultations. Current evaluations often occur after a patient's issue is well-defined, neglecting the init…
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AI scribe fabricates patient history during medical appointment
An AI scribe used during a medical appointment fabricated information, leading to significant distress for a patient. The AI incorrectly stated the patient used psychedelic mushrooms, which the patient vehemently denies…
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AI scribe error devastates patient during medical appointment · 4 sources tracked
An AI scribe made a critical error during a medical appointment, leading to devastating consequences for a patient. The incident, reported by ABC News in Australia, highlights the potential risks and negative impacts of…
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AI model HIPNO infers patient hemodynamics from non-invasive signals
Researchers have developed HIPNO (Hemodynamic Inference via Physics-informed Neural Operators), a novel AI model designed to non-invasively infer hemodynamic states from ubiquitous signals. HIPNO addresses a scale symme…
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New multi-agent system tailors AI explanations for diverse audiences
Researchers have developed XstrAI, a novel multi-agent framework designed to generate audience-aware narratives for explaining AI model predictions, particularly in the medical field. This system treats feature-attribut…
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AI patient simulator separates clinical truth from language generation
A backend engineer and a doctor developed an AI patient simulator that separates clinical truth from language generation. The system maintains a fixed clinical state for each patient, with a knowledge graph providing me…
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Text-to-SQL benchmark errors highlight flawed gold standard
A new analysis of the BIRD-dev text-to-SQL benchmark reveals significant issues with its gold standard SQL annotations, with nearly 20% of model errors stemming from the benchmark incorrectly flagging correct model outp…
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LLMs show a "judgment-consequence gap" in healthcare resource allocation
A new research paper published on arXiv explores the moral reasoning of large language models (LLMs) in healthcare decision-making, specifically concerning the allocation of scarce resources. The study found a significa…
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New protocol aids stroke survivors in defining AI explainability needs
Researchers have developed a video-based protocol to elicit explainable AI (XAI) requirements from stroke survivors, addressing the challenge of communicating complex AI concepts to individuals with communication impair…
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AI tool offers clinicians a 'second pair of eyes' to improve patient care
An artificial intelligence tool designed to assist clinicians by providing a 'second pair of eyes' is being evaluated for its impact on patient care. The effectiveness and benefits of this AI technology in clinical sett…
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AI scribe records and analyzes doctor-patient conversations for note generation
An AI "scribe" listens to conversations between doctors and patients, records them, and then analyzes the dialogue to generate medical notes. This process requires explicit permission from both parties due to the sensit…
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Developer leverages LLM and pre-built schema to generate FHIR data
A developer struggled to manually create a FHIR R4 compliant Patient resource schema in TypeScript for a hospital client, finding the official specification complex and time-consuming to implement correctly. After two d…
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Medical AI training data privacy audit reveals patient identification risks
A new study has performed the first patient-level privacy audit on data used to train medical AI models. The research aimed to determine how easily individual patients could be identified from this underlying data. This…