Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 37,091 to 37,100 of 223,469 articles

Evaluating artificial intelligence caution: ChatGPT's challenges in panoramic radiograph interpretation.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
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Integrative Analysis Combining Machine Learning and Functional Experiments Uncovers ISG15 As a Key Determinant of Cisplatin Resistance in Gastric Cancer.

Anticancer research
BACKGROUND/AIM: Cisplatin resistance remains a major obstacle in advanced gastric cancer (GC). This study aimed to identify key molecular determinants of cisplatin resistance, with a focus on interferon-stimulated genes (ISGs), and to systematically ... read more 

Usefulness of Artificial Intelligence for Surgical Support in Robot-assisted Distal Pancreatectomy: A Preliminary Case Report.

Anticancer research
BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancreatic disease remains a concern. The application of artificial intelligence (AI) in surgery has been reported to improve the precision of anatomical i... read more 

Development and Internal Validation of a Gradient Boosting Model for Pressure Injury Risk in the ICU.

International wound journal
Pressure injury (PI) is common in the ICU and not well captured by single-risk tools such as the Braden scale. We aimed to develop and internally validate a machine-learning model to predict new-onset PI using routinely collected ICU data. This retro... read more 

Single-Cell Transcriptomic Analysis of Chemotherapy-Induced Changes in Osteosarcoma With a Pyroptosis-Related Gene-Based Prognostic Model.

Journal of cellular and molecular medicine
Osteosarcoma, the most common primary malignant bone tumour, presents significant treatment challenges due to its complex tumour microenvironment and the development of chemoresistance. This study employs single-cell transcriptomics to investigate ch... read more 

Multi-Omics and Machine Learning-Driven Discovery of ABCC8 (SUR1) for Diabetes Mellitus: Integrating Molecular Insights on Nigella sativa Bioactives and Sulfonylurea.

Chemical biology & drug design
Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia and pancreatic β-cell dysfunction. The ATP-sensitive potassium KATP channel, regulated by ATP-binding cassette subfamily C member 8 (ABCC8/SUR1), plays a pivotal role in... read more 

Design and Development of an Automated Electroencephalogram Signal Processing and Diagnostic Support Architecture Employing Advanced Deep Learning Models for Early Accurate and Scalable Detection of Neurological Diseases.

Physiotherapy research international : the journal for researchers and clinicians in physical therapy
BACKGROUND AND PURPOSE: Electroencephalogram (EEG) signals play a vital role in analyzing neurological activity and diagnosing various neurological disorders. With the rapid growth of the Internet of medical things (IoMT), EEG-based diagnostic system... read more 

Game Changers in the Treatment of and Engagement With Persons Living With Mental Health and Substance Use Disorders: The Role of the Nurse.

International journal of mental health nursing
The game changers in mental health and substance use disorder treatment have been shaped by historical sea changes marked by transformative advancements that have significantly enhanced patient care. Breakthroughs in psychotherapy, psychosurgery and ... read more 

Investigating the Readability and Quality of AI Systems to Trending Questions About Food Poisoning.

Journal of food science
Consumers increasingly turn to artificial intelligence (AI) systems, including search engines and large language models (LLMs), for immediate food safety guidance. However, the reliability and accessibility of this information for critical public hea... read more 

Predicting Long-Term Depression Progression in Parkinson's Disease: A Machine-Learning Survival Analysis and Risk Score.

CNS neuroscience & therapeutics
BACKGROUND: Depression in Parkinson's disease (dPD) is common and heterogeneous, impairs quality of life, and may accelerate disease progression. Tools that predict long-term dPD progression are lacking. METHODS: We retrospectively analyzed de novo, ... read more