AIMC Topic: Machine Learning

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Revolutionizing enzyme engineering through artificial intelligence and machine learning.

Emerging topics in life sciences
The combinatorial space of an enzyme sequence has astronomical possibilities and exploring it with contemporary experimental techniques is arduous and often ineffective. Multi-target objectives such as concomitantly achieving improved selectivity, so...

Identification of spectral signature for in situ real-time monitoring of smoltification.

Applied optics
We describe the use of an optical hyperspectral sensing technique to identify the smoltification status of Atlantic salmon (Salmo salar) based on spectral signatures, thus potentially providing smolt producers with an additional tool to verify the os...

Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events.

Studies in health technology and informatics
BACKGROUND: Patients with major adverse cardiovascular events (MACE) such as myocardial infarction or stroke suffer from frequent hospitalizations and have high mortality rates. By identifying patients at risk at an early stage, MACE can be prevented...

Fluorescence microscopy datasets for training deep neural networks.

GigaScience
BACKGROUND: Fluorescence microscopy is an important technique in many areas of biological research. Two factors that limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging and, when ima...

Learning graph representations of biochemical networks and its application to enzymatic link prediction.

Bioinformatics (Oxford, England)
MOTIVATION: The complete characterization of enzymatic activities between molecules remains incomplete, hindering biological engineering and limiting biological discovery. We develop in this work a technique, enzymatic link prediction (ELP), for pred...

Predicting candidate genes from phenotypes, functions and anatomical site of expression.

Bioinformatics (Oxford, England)
MOTIVATION: Over the past years, many computational methods have been developed to incorporate information about phenotypes for disease-gene prioritization task. These methods generally compute the similarity between a patient's phenotypes and a data...

Deep Learning in Kidney Ultrasound: Overview, Frontiers, and Challenges.

Advances in chronic kidney disease
Ultrasonography is a practical imaging technique used in numerous health care settings. It is relatively inexpensive, portable, and safe, and it has dynamic capabilities that make it an invaluable tool for a wide variety of diagnostic and interventio...

Use of Artificial Intelligence in Dentistry: Current Clinical Trends and Research Advances.

Journal (Canadian Dental Association)
The field of artificial intelligence (AI) has experienced spectacular development and growth over the past two decades. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding i...

[Exploration on rationality evaluation approach of drug combination medication based on sequential analysis and machine learning].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
Drug combination is a common clinical phenomenon. However, the scientific implementation of drug combination is li-mited by the weak rational evaluation that reflects its clinical characteristics. In order to break through the limitations of existing...

ARTIFICIAL INTELLIGENCE IN MEDICAL DEVICES: PAST, PRESENT AND FUTURE.

Psychiatria Danubina
Artificial Intelligence (AI) has been drawing attention in the field of medical devices. However, due to system complexity, the variability of their architecture, as well as ethical and regulatory concerns there is an ongoing need to analyze its appl...