AIMC Topic: Machine Learning

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Modeling of astaxanthin biosynthesis via machine learning, mathematical and metabolic network modeling.

Critical reviews in biotechnology
Natural astaxanthin is synthesized by diverse organisms including: bacteria, fungi, microalgae, and plants involving complex cellular processes, which depend on numerous interrelated parameters. Nonetheless, existing knowledge regarding astaxanthin b...

Artificial intelligence for dementia drug discovery and trials optimization.

Alzheimer's & dementia : the journal of the Alzheimer's Association
Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data ana...

Using Machine Learning to Identify Predictors of Sexually Transmitted Infections Over Time Among Young People Living With or at Risk for HIV Who Participated in ATN Protocols 147, 148, and 149.

Sexually transmitted diseases
BACKGROUND: Sexually transmitted infections (STIs) among youth aged 12 to 24 years have doubled in the last 13 years, accounting for 50% of STIs nationally. We need to identify predictors of STI among youth in urban HIV epicenters.

Current state and prospects of artificial intelligence in allergy.

Allergy
The field of medicine is witnessing an exponential growth of interest in artificial intelligence (AI), which enables new research questions and the analysis of larger and new types of data. Nevertheless, applications that go beyond proof of concepts ...

A narrative review of recent tools and innovations toward automating living systematic reviews and evidence syntheses.

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
Living reviews are an increasingly popular research paradigm. The purpose of a 'living' approach is to allow rapid collation, appraisal and synthesis of evolving evidence on an important research topic, enabling timely influence on patient care and p...

Advancing AI in healthcare: A comprehensive review of best practices.

Clinica chimica acta; international journal of clinical chemistry
Artificial Intelligence (AI) and Machine Learning (ML) are powerful tools shaping the healthcare sector. This review considers twelve key aspects of AI in clinical practice: 1) Ethical AI; 2) Explainable AI; 3) Health Equity and Bias in AI; 4) Sponso...

Enhanced wave overtopping simulation at vertical breakwaters using machine learning algorithms.

PloS one
Accurate prediction of wave overtopping at sea defences remains central to the protection of lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased risks of rising sea levels and more frequent storm surges, robus...

Evaluating the Use of Graph Neural Networks and Transfer Learning for Oral Bioavailability Prediction.

Journal of chemical information and modeling
Oral bioavailability is a pharmacokinetic property that plays an important role in drug discovery. Recently developed computational models involve the use of molecular descriptors, fingerprints, and conventional machine-learning models. However, dete...

Mammography using low-frequency electromagnetic fields with deep learning.

Scientific reports
In this paper, a novel technique for detecting female breast anomalous tissues is presented and validated through numerical simulations. The technique, to a high degree, resembles X-ray mammography; however, instead of using X-rays for obtaining imag...

Artificial intelligence algorithm comparison and ranking for weight prediction in sheep.

Scientific reports
In a rapidly transforming world, farm data is growing exponentially. Realizing the importance of this data, researchers are looking for new solutions to analyse this data and make farming predictions. Artificial Intelligence, with its capacity to han...