AIMC Topic: Artificial Intelligence

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External Validation of a Commercial Artificial Intelligence Algorithm on a Diverse Population for Detection of False Negative Breast Cancers.

Journal of breast imaging
OBJECTIVE: There are limited data on the application of artificial intelligence (AI) on nonenriched, real-world screening mammograms. This work aims to evaluate the ability of AI to detect false negative cancers not detected at the time of screening ...

Potential Impact of an Artificial Intelligence-based Mammography Triage Algorithm on Performance and Workload in a Population-based Screening Sample.

Journal of breast imaging
OBJECTIVE: To evaluate potential screening mammography performance and workload impact using a commercial artificial intelligence (AI)-based triage device in a population-based screening sample.

The Application Value of an Artificial Intelligence-Driven Intestinal Image Recognition Model to Evaluate Intestinal Preparation before Colonoscopy.

British journal of hospital medicine (London, England : 2005)
Artificial intelligence (AI), with advantages such as automatic feature extraction and high data processing capacity and being unaffected by fatigue, can accurately analyze images obtained from colonoscopy, assess the quality of bowel preparation, a...

Comparing Artificial Intelligence Guided Image Assessment to Current Methods of Burn Assessment.

Journal of burn care & research : official publication of the American Burn Association
Appropriate identification of burn depth and size is paramount. Despite the development of burn depth assessment aids [eg, laser Doppler imaging (LDI)], clinical assessment, which assesses partial-thickness burn depth with 67% accuracy, currently rem...

FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine.

JAMA
IMPORTANCE: Advances in artificial intelligence (AI) must be matched by efforts to better understand and evaluate how AI performs across health care and biomedicine as well as develop appropriate regulatory frameworks. This Special Communication revi...

Evaluating AI Models: Performance Validation Using Formal Multiple-Choice Questions in Neuropsychology.

Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists
High-quality and accessible education is crucial for advancing neuropsychology. A recent study identified key barriers to board certification in clinical neuropsychology, such as time constraints and insufficient specialized knowledge. To address the...

[Legal Risk Assessment and Prevention in Artificial Intelligence-Assisted Health Care].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
With the wide application of new technologies such as large language models and generative artificial intelligence (AI) in the health care sector, artificial intelligence-assisted health care is confronted with new forms of legal risks. The algorithm...

Leveraging artificial intelligence-mediated communication for cancer prevention and control and drug addiction: A systematic review.

Translational behavioral medicine
OBJECTIVE: To conduct a systematic review on Artificial Intelligence-Mediated Communication (AIMC) behavioral interventions in cancer prevention/control and substance use.

AI for all: bridging data gaps in machine learning and health.

Translational behavioral medicine
Artificial intelligence (AI) and its subset, machine learning, have tremendous potential to transform health care, medicine, and population health through improved diagnoses, treatments, and patient care. However, the effectiveness of these technolog...

Physicians' required competencies in AI-assisted clinical settings: a systematic review.

British medical bulletin
BACKGROUND: Utilizing Artificial Intelligence (AI) in clinical settings may offer significant benefits. A roadblock to the responsible implementation of medical AI is the remaining uncertainty regarding requirements for AI users at the bedside. An ov...