AIMC Topic: Cost-Benefit Analysis

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Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain.

Journal of medical economics
OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...

Practical considerations for implementation of syndromic panel and diagnostic stewardship in the era of syndromic panel testing.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: The significant advancements in the development of syndromic panel testing for infectious diseases have brought about a paradigm shift in the clinical microbiology laboratory and the practices of Infectious Diseases Physicians. Due to the...

Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine coronary computed tomography angiography.

European heart journal. Quality of care & clinical outcomes
AIMS: Coronary computed tomography angiography (CCTA) is a first-line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We as...

Clinical and economic effectiveness of Schroth therapy in adolescent idiopathic scoliosis: insights from a machine learning- and active learning-based real-world study.

Journal of orthopaedic surgery and research
BACKGROUND: Adolescent idiopathic scoliosis (AIS) is a prevalent musculoskeletal condition affecting approximately 2-3% of the adolescent population. Although exercise-based therapeutic interventions are increasingly employed as non-surgical alternat...

Balancing accuracy and cost in machine learning models for detecting medial vascular calcification in chronic kidney disease: a pilot study.

Scientific reports
Machine learning algorithms that integrate multiple biomarkers are increasingly used in disease detection, yet economic considerations are often overlooked. Medial vascular calcification (mVC), a pathology associated with elevated cardiovascular risk...

A cost-effective approach using generative AI and gamification to enhance biomedical treatment and real-time biosensor monitoring.

Scientific reports
Biosensors are crucial to the diagnosis process since they are designed to detect a specific biological analyte by changing from a biological entity into electrical signals that can be processed for further inspection and analysis. The method provide...

Cost-effectiveness of opportunistic osteoporosis screening using chest radiographs with deep learning in Germany.

Aging clinical and experimental research
BACKGROUND: Osteoporosis is often underdiagnosed due to limitations in traditional screening methods, leading to missed early intervention opportunities. AI-driven screening using chest radiographs could improve early detection, reduce fracture risk,...

Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation.

Health technology assessment (Winchester, England)
BACKGROUND: Lung cancer is one of the most common types of cancer and the leading cause of cancer death in the United Kingdom. Artificial intelligence-based software has been developed to reduce the number of missed or misdiagnosed lung nodules on co...