AIMC Topic: Machine Learning

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An explainable deep learning-based algorithm with an attention mechanism for predicting the live birth potential of mouse embryos.

Artificial intelligence in medicine
In assisted reproductive technology (ART), embryos produced by in vitro fertilization (IVF) are graded according to their live birth potential, and high-grade embryos are preferentially transplanted. However, rates of live birth following clinical AR...

A Review on Data Fusion of Multidimensional Medical and Biomedical Data.

Molecules (Basel, Switzerland)
Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characteriz...

Self-supervised machine learning for live cell imagery segmentation.

Communications biology
Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the advent of machine learning (ML) methods to aid in this process, the overwhelming majority of which fall u...

Assessing incentives to increase digital payment acceptance and usage: A machine learning approach.

PloS one
An important step to achieve greater financial inclusion is to increase the acceptance and usage of digital payments. Although consumer adoption of digital payments has improved dramatically globally, the acceptance and usage of digital payments for ...

Machine Learning Diffusion Monte Carlo Energies.

Journal of chemical theory and computation
We present two machine learning methodologies that are capable of predicting diffusion Monte Carlo (DMC) energies with small data sets (≈60 DMC calculations in total). The first uses voxel deep neural networks (VDNNs) to predict DMC energy densities ...

Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison.

BMC medical research methodology
BACKGROUND: There is growing enthusiasm for the application of machine learning (ML) and artificial intelligence (AI) techniques to clinical research and practice. However, instructions on how to develop robust high-quality ML and AI in medicine are ...

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models.

Scientific reports
Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation that offer great promise for various clinical modalities. As with other types of radiation, the therapeutic efficacy and safety of low-temperature plasm...

A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair.

PloS one
INTRODUCTION: The use of biologic adjuvants (orthobiologics) is becoming commonplace in orthopaedic surgery. Among other applications, biologics are often added to enhance fusion rates in spinal surgery and to promote bone healing in complex fracture...