AIMC Topic: Machine Learning

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Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics.

Journal of sport and health science
BACKGROUND: Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo, and the characteristics of different types of impacts are...

Evaluation of the Morphological and Biological Functions of Vascularized Microphysiological Systems with Supervised Machine Learning.

Annals of biomedical engineering
Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level fe...

Can We Quickly Learn to "Translate" Bioactive Molecules with Transformer Models?

Journal of chemical information and modeling
Meaningful exploration of the chemical space of druglike molecules in drug design is a highly challenging task due to a combinatorial explosion of possible modifications of molecules. In this work, we address this problem with transformer models, a t...

Bacteria-Specific Feature Selection for Enhanced Antimicrobial Peptide Activity Predictions Using Machine-Learning Methods.

Journal of chemical information and modeling
There are several classes of short peptide molecules, known as antimicrobial peptides (AMPs), which are produced during the immune responses of living organisms against various infections. In recent years, substantial progress has been achieved in ap...

Benchmarking machine learning robustness in Covid-19 genome sequence classification.

Scientific reports
The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional ap...

A machine learning based approach for quantitative evaluation of cell migration in Transwell assays based on deformation characteristics.

The Analyst
Many pathological and physiological processes, including embryonic development, immune response and cancer metastasis, involve studies on cell migration, and especially detection methods, for which it is difficult to satisfy the requirements for rapi...

Automating Quality Assessment of Medical Evidence in Systematic Reviews: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Assessment of the quality of medical evidence available on the web is a critical step in the preparation of systematic reviews. Existing tools that automate parts of this task validate the quality of individual studies but not of entire b...

Forecasting and Optimizing Dual Media Filter Performance via Machine Learning.

Water research
Four different machine learning algorithms, including Decision Tree (DT), Random Forest (RF), Multivariable Linear Regression (MLR), Support Vector Regressions (SVR), and Gaussian Process Regressions (GPR), were applied to predict the performance of ...

Gender classification from anthropometric measurement by boosting decision tree: A novel machine learning approach.

Journal of the National Medical Association
The decision tree used a generating set of rules based on various correlated variables for developing an algorithm from the target variable. Using the training dataset this paper used boosting tree algorithm for gender classification from twenty-five...