AIMC Topic: Machine Learning

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Advances, trends and challenges in the use of biochar as an improvement strategy in the anaerobic digestion of organic waste: a systematic analysis.

Bioengineered
A recently strategy applied to anaerobic digestion (AD) is the use of biochar (BC) obtained from the pyrolysis of different organic waste. The PRISMA protocol-based review of the most recent literature data from 2011-2022 was used in this study. The ...

Using machine learning to predict bleeding after cardiac surgery.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The primary objective was to predict bleeding after cardiac surgery with machine learning using the data from the Australia New Zealand Society of Cardiac and Thoracic Surgeons Cardiac Surgery Database, cardiopulmonary bypass perfusion da...

ChatGPT in medical school: how successful is AI in progress testing?

Medical education online
BACKGROUND: As generative artificial intelligence (AI), ChatGPT provides easy access to a wide range of information, including factual knowledge in the field of medicine. Given that knowledge acquisition is a basic determinant of physicians' performa...

Interpretable predictive models of genome-wide aryl hydrocarbon receptor-DNA binding reveal tissue-specific binding determinants.

Toxicological sciences : an official journal of the Society of Toxicology
The aryl hydrocarbon receptor (AhR) is an inducible transcription factor whose ligands include the potent environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Ligand-activated AhR binds to DNA at dioxin response elements (DREs) conta...

Perspective of Signal Processing-Based on Brain-Computer Interfaces Using Machine Learning Methods.

Studies in health technology and informatics
The application of artificial intelligence (AI) algorithms is an indispensable portion of developing brain-computer interfaces (BCI). With the continuous development of AI concepts and related technologies. AI algorithms such as neural networks play ...

From beasts to bytes: Revolutionizing zoological research with artificial intelligence.

Zoological research
Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological res...

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Development of electronic health records (EHR)-based machine learning models for pediatric inpatients is challenged by limited training data. Self-supervised learning using adult data may be a promising approach to creating robust pediatri...

Artificial Intelligence: Basics, Impact, and How Nurses Can Contribute.

Clinical journal of oncology nursing
Applying artificial intelligence (AI) to cancer care has the potential to transform and enhance nursing practice and patient outcomes, from cancer prevention and screening through treatment, survivorship, and end-of-life care.