AIMC Topic: Disease Management

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ChatGPT enters the room: what it means for patient counseling, physician education, academics, and disease management.

Current opinion in ophthalmology Feb 7, 2024
PURPOSE OF REVIEW: This review seeks to provide a summary of the most recent research findings regarding the utilization of ChatGPT, an artificial intelligence (AI)-powered chatbot, in the field of ophthalmology in addition to exploring the limitatio...
Physicians Educational Status Humans Disease Management Artificial Intelligence Counseling
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Advanced deep learning techniques for early disease prediction in cauliflower plants.

Scientific reports Oct 27, 2023
Agriculture plays a pivotal role in the economies of developing countries by providing livelihoods, sustenance, and employment opportunities in rural areas. However, crop diseases pose a significant threat to both farmers' incomes and food security. ...
Deep Learning Agriculture Drug-Related Side Effects and Adverse Reactions Disease Management Humans Empirical Research
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Evaluating the Diagnostic Accuracy and Management Recommendations of ChatGPT in Uveitis.

Ocular immunology and inflammation Sep 18, 2023
INTRODUCTION: Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice...
Diagnostic Techniques, Ophthalmological Ophthalmologists Female Reproducibility of Results Male Uveitis Disease Management Diagnosis, Differential Humans Ophthalmology Artificial Intelligence
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Treatment Effect Heterogeneity.

Evaluation review May 29, 2022
This paper considers recent methodological developments in the treatment effects literature, describes their value for applied evaluation work, and suggests next steps. It pays particular attention to documenting the presence of treatment effect hete...
Disease Management Humans Machine Learning
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A Systematic Review of Artificial Intelligence Applications Used for Inherited Retinal Disease Management.

Medicina (Kaunas, Lithuania) Mar 31, 2022
Nowadays, Artificial Intelligence (AI) and its subfields, Machine Learning (ML) and Deep Learning (DL), are used for a variety of medical applications. It can help clinicians track the patient's illness cycle, assist with diagnosis, and offer appropr...
Humans Artificial Intelligence Machine Learning Disease Management Retinal Diseases
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Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare.

Current medical science Dec 24, 2021
Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the "Smart Healthcare" ...
Inventions Blockchain Wearable Electronic Devices Chronic Disease Disease Management Artificial Intelligence Delivery of Health Care Humans
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Development and validation of a practical machine-learning triage algorithm for the detection of patients in need of critical care in the emergency department.

Scientific reports Dec 15, 2021
Identifying critically ill patients is a key challenge in emergency department (ED) triage. Mis-triage errors are still widespread in triage systems around the world. Here, we present a machine learning system (MLS) to assist ED triage officers bette...
Triage Area Under Curve Emergency Service, Hospital Critical Care Male Middle Aged ROC Curve Disease Management Odds Ratio Disease Susceptibility Machine Learning Algorithms Critical Illness Humans Aged Adult Clinical Decision-Making Female
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Decision making on vestibular schwannoma treatment: predictions based on machine-learning analysis.

Scientific reports Sep 15, 2021
Decision making on the treatment of vestibular schwannoma (VS) is mainly based on the symptoms, tumor size, patient's preference, and experience of the medical team. Here we provide objective tools to support the decision process by answering two que...
Neuroma, Acoustic Hearing Symptom Assessment Hearing Tests Adult Supervised Machine Learning Female Humans ROC Curve Male Disease Management Reproducibility of Results Machine Learning Decision Trees Middle Aged Aged Clinical Decision-Making
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Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.

Scientific reports Sep 15, 2021
Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting older patients' one-year risk of acute coronary syndrome and death following the use of non-steroidal ...
Acute Coronary Syndrome Proportional Hazards Models Disease Susceptibility Area Under Curve Humans Machine Learning Cause of Death Disease Management Models, Theoretical Prognosis Comorbidity Australia Male Female ROC Curve Anti-Inflammatory Agents, Non-Steroidal Risk Assessment Risk Factors
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Geometric and biomechanical modeling aided by machine learning improves the prediction of growth and rupture of small abdominal aortic aneurysms.

Scientific reports Sep 10, 2021
It remains difficult to predict when which patients with abdominal aortic aneurysm (AAA) will require surgery. The aim was to study the accuracy of geometric and biomechanical analysis of small AAAs to predict reaching the threshold for surgery, diam...
Algorithms Prognosis Humans Machine Learning Aorta, Abdominal Computed Tomography Angiography Models, Cardiovascular ROC Curve Tomography, X-Ray Computed Aortic Rupture Aortic Aneurysm, Abdominal Clinical Decision-Making Area Under Curve Biomechanical Phenomena Disease Management
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