AIMC Topic: Adult

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Exploring the potential of artificial intelligence models for triage in the emergency department.

Postgraduate medicine
OBJECTIVE: To perform a comparative analysis of the three-level triage protocol conducted by triage nurses and emergency medicine doctors with the use of ChatGPT, Gemini, and Pi, which are recognized artificial intelligence (AI) models widely used in...

Semiology Extraction and Machine Learning-Based Classification of Electronic Health Records for Patients With Epilepsy: Retrospective Analysis.

JMIR medical informatics
BACKGROUND: Obtaining and describing semiology efficiently and classifying seizure types correctly are crucial for the diagnosis and treatment of epilepsy. Nevertheless, there exists an inadequacy in related informatics resources and decision support...

Assessment of autostereoscopic perception using artificial intelligence-enhanced face tracking technology.

PloS one
PURPOSE: Stereopsis, the ability of humans to perceive depth through distinct visual stimuli in each eye, is foundational to autostereoscopic technology in computing. However, ensuring stable head position during assessments has been challenging. Thi...

Developing a Wearable Sensor-Based Digital Biomarker of Opioid Dependence.

Anesthesia and analgesia
BACKGROUND: Repeated opioid exposure leads to a variety of physiologic adaptations that develop at different rates and may foreshadow risk of opioid-use disorder (OUD), including dependence and withdrawal. Digital pharmacovigilance strategies that us...

Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis.

European radiology
OBJECTIVES: To evaluate the value of a magnetic resonance imaging (MRI)-based deep learning radiomic nomogram (DLRN) for distinguishing intracranial solitary fibrous tumors (ISFTs) from angiomatous meningioma (AMs) and predicting overall survival (OS...

Automatic Hardy and Clapham's classification of hallux sesamoid position on foot radiographs using deep neural network.

Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons
BACKGROUND: There is currently no deep neural network (DNN) capable of automatically classifying tibial sesamoid position (TSP) on foot radiographs.

Rapid On-Site Histology of Lung and Pleural Biopsies Using Higher Harmonic Generation Microscopy and Artificial Intelligence Analysis.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Lung cancer is one of the most prevalent and lethal cancers. To improve health outcomes while reducing health care burden, it becomes crucial to move toward early detection and cost-effective workflows. Currently, there is no method for the on-site r...

Multiparametric MRI Radiomics With Machine Learning for Differentiating HER2-Zero, -Low, and -Positive Breast Cancer: Model Development, Testing, and Interpretability Analysis.

AJR. American journal of roentgenology
MRI radiomics has been explored for three-tiered classification of HER2 expression levels (i.e., HER2-zero, HER2-low, or HER2-positive) in patients with breast cancer, although an understanding of how such models reach their predictions is lacking. ...

The impact of artificial intelligence on the knowledge, attitude, and practice of pharmacists across diverse settings: A cross-sectional study.

International journal of medical informatics
The pharmacy practice landscape is undergoing a significant transformation with the increasing integration of artificial intelligence (AI). As essential members of the healthcare team, pharmacists' readiness and willingness to adopt AI technologies i...

Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

PloS one
Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a serious threat to world health. The TB diagnosis phase includes a patient's medical history, physic...