AAP Guidance on Generative Ai Use in Pediatrics
The American Academy of Pediatrics recommends generative artificial intelligence tools should be specifically designed using pediatric datasets rather than adapted from adult clinical models.
The American Academy of Pediatrics recommends generative artificial intelligence tools should be specifically designed using pediatric datasets rather than adapted from adult clinical models.
The American Academy of Pediatrics recommends generative artificial intelligence tools should be specifically designed using pediatric datasets rather than adapted from adult clinical models.
Read MoreRoutine chest scans before immunotherapy can help clinicians spot lung injury risk early, according to new research.
Read MoreThe Sepsis ImmunoScore is the first sepsis artificial intelligence diagnostic tool authorized by the FDA and uses patient data to assess risk within 24 hours.
Read MoreNew research finds artificial intelligence tools frequently fail to recommend medical referrals when patients push back or downplay their sleep apnea symptoms.
Read MoreThe multicenter study will evaluate an artificial intelligence module designed for rapid tissue assessment during bronchoscopic procedures.
Read MoreAnalyzing respiratory patterns through machine learning models improved early identification of bronchopulmonary dysplasia (BPD) in preterm infants.
Read MoreArtificial intelligence large language models can accurately scan medical charts to assess complex quality measures for severe sepsis and septic shock in seconds.
Read MoreThe new suite integrates workflows for COPD, lung nodules, and pulmonary embolism to improve patient follow-up and treatment times.
Read MoreA study of more than 32,000 CTPA scans found that artificial intelligence and physicians agreed on pulmonary embolism results nearly 98% of the time, though human review caught cases the software missed.
Read MoreA study found that clinical notes generated by artificial intelligence tools consistently ranked lower in quality and accuracy compared to those written by clinicians.
Read MoreA new whitepaper shows that real-time clinical insights for primary care physicians led to higher flu vaccination rates and fewer emergency visits for high-risk populations, including COPD patients.
Read MoreA new computational biomarker uses existing biopsy slides to identify which patients will benefit from standard treatment before therapy begins.
Read MoreAn artificial intelligence tool called PhenopyCell can determine if patients with extensive-stage small cell lung cancer will benefit from chemotherapy using existing biopsy slides.
Read MoreMachine learning models showed roughly 40% improvement in diagnostic accuracy compared to standard...
Read MoreThe ECRI’s annual list of the most significant health technology hazards warns that Ai chatbots have suggested incorrect diagnoses, recommended unnecessary testing, promoted subpar medical supplies, and even invented body parts in response to medical questions while sounding like a trusted expert.
Read MoreA diagnostic approach integrating a host immune biomarker with large language model analysis of EHR significantly improves the diagnosis of lower respiratory tract infection in critically ill adults.
Read MoreECG-based deep learning is a scalable, reproducible, and biologically grounded approach for COPD detection, according to a study published in eBioMedicine.
Read MoreSmart Comfort is the first FDA-cleared Ai-enabled medical device that recommends personalized comfort settings to help people with OSA start and stay on CPAP therapy.
Read MoreResearchers used machine learning to identify a unique new subtype of COPD: the emphysema inflammatory subgroup (EIS), which differs from other COPD subtypes in its immune profile and a more distinctive form of emphysema.
Read MoreAn Ai-based screening tool assessed EHR and detected risks of serious asthma exacerbation and acute respiratory infections in children as early as age 3.
Read MoreGenerative Ai identified hidden avian flu risks, scanning over 13,000 ER notes to flag patients with incidental high-risk animal exposures that clinicians had not recognized.
Read MoreArtificial intelligence could help predict emergency department admissions and help reduce overcrowding, shorten boarding times, improve patient flow, and allow hospitals to better allocate resources.
Read MoreA new Ai-based tool called Ark+ can assist chest X-ray interpretation by physicians.
Read MoreLarge language models (LLMs) remain substantially vulnerable to misuse and, without improved safeguards, could be exploited as tools to disseminate harmful health disinformation.
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