AI Medical Compendium Topic

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Big Data

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Cognitive analysis of metabolomics data for systems biology.

Nature protocols
Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. M...

Machine Learning for Clinical Outcome Prediction.

IEEE reviews in biomedical engineering
Clinical decision-making in healthcare is already being influenced by predictions or recommendations made by data-driven machines. Numerous machine learning applications have appeared in the latest clinical literature, especially for outcome predicti...

Automatic segmentation of white matter hyperintensities from brain magnetic resonance images in the era of deep learning and big data - A systematic review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: White matter hyperintensities (WMH), of presumed vascular origin, are visible and quantifiable neuroradiological markers of brain parenchymal change. These changes may range from damage secondary to inflammation and other neurological con...

Evaluating the sustainability of big data centers using the analytic network process and fuzzy TOPSIS.

Environmental science and pollution research international
The big data revolution has created data center sustainability problems, whose solutions require the consideration of environmental factors. The purpose of this study is to establish a big data center sustainability evaluation index and provide guida...

Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data.

Journal of plant physiology
Highly efficient and accurate selection of elite genotypes can lead to dramatic shortening of the breeding cycle in major crops relevant for sustaining present demands for food, feed, and fuel. In contrast to classical approaches that emphasize the n...

For a critical appraisal of artificial intelligence in healthcare: The problem of bias in mHealth.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Artificial intelligence and big data are more and more used in medicine, either in prevention, diagnosis or treatment, and are clearly modifying the way medicine is thought and practiced. Some authors argue that the us...

Anomaly Identification during Polymerase Chain Reaction for Detecting SARS-CoV-2 Using Artificial Intelligence Trained from Simulated Data.

Molecules (Basel, Switzerland)
Real-time reverse transcription (RT) PCR is the gold standard for detecting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), owing to its sensitivity and specificity, thereby meeting the demand for the rising number of cases. The scarcit...

Intelligence Is beyond Learning: A Context-Aware Artificial Intelligent System for Video Understanding.

Computational intelligence and neuroscience
Understanding video files is a challenging task. While the current video understanding techniques rely on deep learning, the obtained results suffer from a lack of real trustful meaning. Deep learning recognizes patterns from big data, leading to dee...

Assessing Drug Development Risk Using Big Data and Machine Learning.

Cancer research
Identifying new drug targets and developing safe and effective drugs is both challenging and risky. Furthermore, characterizing drug development risk, the probability that a drug will eventually receive regulatory approval, has been notoriously hard ...