AIMC Topic: Machine Learning

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In silico co-crystal design: Assessment of the latest advances.

Drug discovery today
Pharmaceutical co-crystals represent a growing class of crystal forms in the context of pharmaceutical science. They are attractive to pharmaceutical scientists because they significantly expand the number of crystal forms that exist for an active ph...

Forecasting actual evapotranspiration without climate data based on stacked integration of DNN and meta-heuristic models across China from 1958 to 2021.

Journal of environmental management
As a non-linear phenomenon that varies along with agro-climatic conditions alongside many other factors, Evapotranspiration (ET) process represents a complexity when be assessed especially if there is a data scarcity in the weather data. However, eve...

Ethical considerations for the use of artificial intelligence in medical decision-making capacity assessments.

Psychiatry research
The rapid advancement of artificial intelligence (AI) and machine learning are providing new tools to clinicians. AI tools have the potential to process vast amounts of data in a short amount of time, providing new insights and changing how we approa...

Treatment response to spironolactone in patients with heart failure with preserved ejection fraction: a machine learning-based analysis of two randomized controlled trials.

EBioMedicine
BACKGROUND: Whether there is a subset of patients with heart failure with preserved ejection fraction (HFpEF) that benefit from spironolactone therapy is unclear. We applied a machine learning approach to identify responders and non-responders to spi...

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

Journal of chemical information and modeling
The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inf...

Rapid Discrimination of ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning.

Transboundary and emerging diseases
The goal of this study was to evaluate matrix-assisted laser desorption ionization-iime of flight mass spectrometry (MALDI-TOF MS) and Fourier-transform infrared spectroscopy (FTIR-S) as diagnostic alternatives to DNA-based methods for the detection ...

Optimal selection of learning data for highly accurate QSAR prediction of chemical biodegradability: a machine learning-based approach.

SAR and QSAR in environmental research
Prior to the manufacture of new chemicals, regulations mandate a thorough review of the chemicals under risk management. This review involves evaluating their effects on the environment and human health. To assess these effects, a review report that ...

Dose reduction and toxicity of lenalidomide-dexamethasone in multiple myeloma: A machine-learning prediction model.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
PURPOSE: Lenalidomide remains an effective drug for multiple myeloma, but it is often associated with adverse events and requires dose adjustments. The objective of this study was to propose a model for predicting whether a patient would require dose...

Orthodontic craniofacial pattern diagnosis: cephalometric geometry and machine learning.

Medical & biological engineering & computing
Efficient and reliable diagnosis of craniofacial patterns is critical to orthodontic treatment. Although machine learning (ML) is time-saving and high-precision, prior knowledge should validate its reliability. This study proposed a craniofacial ML d...

Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed.

Journal of environmental management
Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nutrient concentrations in water resources has gained significant attention during recent decades. Mac...