Clinical chemistry and laboratory medicine
Nov 3, 2022
OBJECTIVES: The field of artificial intelligence (AI) has grown in the past 10 years. Despite the crucial role of laboratory diagnostics in clinical decision-making, we found that the majority of AI studies focus on surgery, radiology, and oncology, ...
A dynamic treatment regime (DTR) is a sequence of decision rules that provide guidance on how to treat individuals based on their static and time-varying status. Existing observational data are often used to generate hypotheses about effective DTRs. ...
Machine learning models are increasingly adopted for facilitating clinical decision-making. However, recent research has shown that machine learning techniques may result in potential biases when making decisions for people in different subgroups, wh...
Artificial Intelligence (AI) systems are precious support for decision-making, with many applications also in the medical domain. The interaction between MDs and AI enjoys a renewed interest following the increased possibilities of deep learning devi...
Machine learning (ML) and artificial intelligence (AI) are widely used in many different fields of modern medicine. This narrative review gives, in the first part, a brief overview of the methods of ML and AI used in patient blood management (PBM) an...
OBJECTIVE: Applications of artificial intelligence (AI) have been reported in several cardiovascular diseases but its interest in patients with peripheral artery disease (PAD) has been so far less reported. The aim of this review was to summarize cur...
Journal of evaluation in clinical practice
Jun 27, 2022
As big data becomes more publicly accessible, artificial intelligence (AI) is increasingly available and applicable to problems around clinical decision-making. Yet the adoption of AI technology in healthcare lags well behind other industries. The ga...
OBJECTIVE: To analyze the critical alarms predictors of clinical deterioration/sepsis for clinical decision making in patients admitted to a reference hospital complex.
Neurocritical care patients are a complex patient population, and to aid clinical decision-making, many models and scoring systems have previously been developed. More recently, techniques from the field of machine learning have been applied to neuro...
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