AIMC Topic: Machine Learning

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Clinical decision support for severe trauma patients: Machine learning based definition of a bundle of care for hemorrhagic shock and traumatic brain injury.

The journal of trauma and acute care surgery
BACKGROUND: Deviation from guidelines is frequent in emergency situations, and this may lead to increased mortality. Probably because of time constraints, 55% is the greatest reported guidelines compliance rate in severe trauma patients. This study a...

Hubness weighted SVM ensemble for prediction of breast cancer subtypes.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Breast cancer is a major disease causing panic among women worldwide. Since gene mutations are the root cause for cancer development, analyzing gene expressions can give more insights into various phenotype of cancer treatments. Breast Ca...

Application of Combined Prediction Model Based on Core and Coritivity Theory in Continuous Blood Pressure Prediction.

Combinatorial chemistry & high throughput screening
BACKGROUND AND OBJECTIVE: Blood pressure is vital evidence for clinicians to predict diseases and check the curative effect of diagnosis and treatment. To further improve the prediction accuracy of blood pressure, this paper proposes a combined predi...

Recent Progress of Machine Learning in Gene Therapy.

Current gene therapy
With new developments in biomedical technology, it is now a viable therapeutic treatment to alter genes with techniques like CRISPR. At the same time, it is increasingly cheaper to perform whole genome sequencing, resulting in rapid advancement in ge...

DL-SMILES#: A Novel Encoding Scheme for Predicting Compound Protein Affinity Using Deep Learning.

Combinatorial chemistry & high throughput screening
INTRODUCTION: Drug repositioning aims to screen drugs and therapeutic goals from approved drugs and abandoned compounds that have been identified as safe. This trend is changing the landscape of drug development and creating a model of drug repositio...

A Survey on Machine Learning Based Medical Assistive Systems in Current Oncological Sciences.

Current medical imaging
BACKGROUND: Cancer is one of the life-threatening diseases which is affecting a large number of population worldwide. Cancer cells multiply inside the body without showing much symptoms on the surface of the skin, thereby making it difficult to predi...

The potential applications of artificial intelligence in drug discovery and development.

Physiological research
Development of a new dug is a very lengthy and highly expensive process since only preclinical, pharmacokinetic, pharmacodynamic and toxicological studies include a multiple of in silico, in vitro, in vivo experimentations that traditionally last sev...

Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases Testing.

Clinical chemistry
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are poised to transform infectious disease testing. Uniquely, infectious disease testing is technologically diverse spaces in laboratory medicine, where multiple platforms and approac...

Trust in AI: why we should be designing for APPROPRIATE reliance.

Journal of the American Medical Informatics Association : JAMIA
Use of artificial intelligence in healthcare, such as machine learning-based predictive algorithms, holds promise for advancing outcomes, but few systems are used in routine clinical practice. Trust has been cited as an important challenge to meaning...

Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future.

Reviews in cardiovascular medicine
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as Machine Learning, and its subtype Deep Learning. AI has incorporated itself in the field of cardiovascular medicine, and increasingly employed to revolutioni...