AI Medical Compendium Topic

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Perspectives on Big Data and Big Data Analytics in Healthcare.

Perspectives in health information management
Big data (BD) is of high interest for research and practice purposes because it has the potential to provide insights into the population served and healthcare practices. Much progress has been made in collecting BD and creating tools for big data an...

Data science and automation in the process of theorizing: Machine learning's power of induction in the co-duction cycle.

PloS one
Recent calls to take up data science either revolve around the superior predictive performance associated with machine learning or the potential of data science techniques for exploratory data analysis. Many believe that these strengths come at the c...

Advancing Clinical Information Systems: Harnessing Telemedicine, Data Science, and AI for Enhanced and More Precise Healthcare Delivery.

Yearbook of medical informatics
OBJECTIVE: In this synopsis, the editors of the Clinical Information Systems (CIS) section of the IMIA Yearbook of Medical Informatics overview recent research and propose a selection of best papers published in 2023 in the CIS field.

Selection of data analytic techniques by using fuzzy AHP TOPSIS from a healthcare perspective.

BMC medical informatics and decision making
The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with differen...

Multimodal representation learning for medical analytics - a systematic literature review.

Health informatics journal
Machine learning-based analytics over uni-modal medical data has shown considerable promise and is now routinely deployed in diagnostic procedures. However, patient data consists of diverse types of data. By exploiting such data, multimodal approach...

Health Care Professionals and Data Scientists' Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study.

Journal of medical Internet research
BACKGROUND: Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantia...

Challenges of reproducible AI in biomedical data science.

BMC medical genomics
Artificial intelligence (AI) is revolutionizing biomedical data science at an unprecedented pace, transforming various aspects of the field with remarkable speed and depth. However, a critical issue remains unclear: how reproducible are the AI models...

Artificial intelligence for modelling infectious disease epidemics.

Nature
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social sci...

A Hands-On Introduction to Data Analytics for Biomedical Research.

Function (Oxford, England)
Artificial intelligence (AI) applications are having increasing impacts in the biomedical sciences. Modern AI tools enable uncovering hidden patterns in large datasets, forecasting outcomes, and numerous other applications. Despite the availability a...

Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.

Briefings in bioinformatics
The development of single-cell and spatial transcriptomics has revolutionized our capacity to investigate cellular properties, functions, and interactions in both cellular and spatial contexts. Despite this progress, the analysis of single-cell and s...