AIMC Topic: Aged

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Machine learning based seizure classification and digital biosignal analysis of ECT seizures.

Scientific reports
While artificial intelligence has received considerable attention in various medical fields, its application in the field of electroconvulsive therapy (ECT) remains rather limited. With the advent of digital seizure collection systems, the developmen...

Perspectives of Black, Latinx, Indigenous, and Asian Communities on Health Data Use and AI: Cross-Sectional Survey Study.

Journal of medical Internet research
Despite excitement around artificial intelligence (AI)-based tools in health care, there is work to be done before they can be equitably deployed. The absence of diverse patient voices in discussions on AI is a pressing matter, and current studies ha...

Artificial intelligence in neurovascular decision-making: a comparative analysis of ChatGPT-4 and multidisciplinary expert recommendations for unruptured intracranial aneurysms.

Neurosurgical review
In the multidisciplinary treatment of cerebrovascular diseases, specialists from different disciplines strive to develop patient-specific treatment recommendations. ChatGPT is a natural language processing chatbot with increasing applicability in med...

Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms.

Frontiers in public health
BACKGROUND: It has been increasingly recognized that adults living alone have a higher likelihood of developing Major Depressive Disorder (MDD) than those living with others. However, there is still no prediction model for MDD specifically designed f...

Plasma Cytokine and Chemokine Profiles Predict Efficacy and Toxicity of Anti-CD19 CAR-T Cell Therapy in Large B-Cell Lymphoma.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: Anti-CD19 chimeric antigen receptor T-cell (CAR-T) therapy has emerged as a promising treatment for large B-cell lymphoma (LBCL); however, durable complete responses are achieved in only 30% to 40% of patients. Additionally, CAR-T therapy...

Diastolic Versus Systolic or Mean Intraoperative Hypotension as Predictive of Perioperative Myocardial Injury in a White-Box Machine-Learning Model.

Anesthesia and analgesia
BACKGROUND: Intraoperative hypotension (IOH) and tachycardia are associated with perioperative myocardial injury (PMI), and thereby increased postoperative mortality. Patients undergoing vascular surgery are specifically at risk of developing cardiac...

Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging: a comprehensive deep learning study.

European journal of nuclear medicine and molecular imaging
BACKGROUND: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a well-established modality for noninvasive diagnostic assessment of coronary artery disease (CAD). However, the time-consuming and experience-...

Artificial intelligence-based model to predict recurrence after local excision in T1 rectal cancer.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: According to current guideline, patients with resected specimens showing high-risk features are recommended additional surgery after local excision (LE) of T1 colorectal cancer, despite the low incidence of recurrence. However, surgical r...

System for Predicting Neurological Outcomes Following Cardiac Arrest Based on Clinical Predictors Using a Machine Learning Method: The Neurological Outcomes After Cardiac Arrest Method.

Neurocritical care
BACKGROUND: A multimodal approach may prove effective for predicting clinical outcomes following cardiac arrest (CA). We aimed to develop a practical predictive model that incorporates clinical factors related to CA and multiple prognostic tests usin...