AIMC Topic: Machine Learning

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Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Scientific reports
Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment, such as extracellular matrix remodeling, reciprocal signaling interactions with cancer cells and crosstalk with infiltrating inflammatory cells. How...

Predicting pediatric anxiety from the temporal pole using neural responses to emotional faces.

Scientific reports
A prominent cognitive aspect of anxiety is dysregulation of emotional interpretation of facial expressions, associated with neural activity from the amygdala and prefrontal cortex. We report machine learning analysis of fMRI results supporting a key ...

Syntax-based transfer learning for the task of biomedical relation extraction.

Journal of biomedical semantics
BACKGROUND: Transfer learning aims at enhancing machine learning performance on a problem by reusing labeled data originally designed for a related, but distinct problem. In particular, domain adaptation consists for a specific task, in reusing train...

Machine learning for manually-measured water quality prediction in fish farming.

PloS one
Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer's decision-ma...

Sexing white 2D footprints using convolutional neural networks.

PloS one
Footprints are left, or obtained, in a variety of scenarios from crime scenes to anthropological investigations. Determining the sex of a footprint can be useful in screening such impressions and attempts have been made to do so using single or multi...

Mapping the spatial and temporal variability of flood hazard affected by climate and land-use changes in the future.

Journal of environmental management
The predicts current and future flood risk in the Kalvan watershed of northwestern Markazi Province, Iran. To do this, 512 flood and non-flood locations were identified and mapped. Twenty flood-risk factors were selected to model flood risk using sev...

Automated detection and explainability of pathological gait patterns using a one-class support vector machine trained on inertial measurement unit based gait data.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Machine learning approaches for the classification of pathological gait based on kinematic data, e.g. derived from inertial sensors, are commonly used in terms of a multi-class classification problem. However, there is a lack of research ...

Machine Learning Directed Optimization of Classical Molecular Modeling Force Fields.

Journal of chemical information and modeling
Accurate force fields are necessary for predictive molecular simulations. However, developing force fields that accurately reproduce experimental properties is challenging. Here, we present a machine learning directed, multiobjective optimization wor...

Machine Learning-Enabled Pipeline for Large-Scale Virtual Drug Screening.

Journal of chemical information and modeling
Virtual screening is receiving renewed attention in drug discovery, but progress is hampered by challenges on two fronts: handling the ever-increasing sizes of libraries of drug-like compounds and separating true positives from false positives. Here,...

Artificial Intelligence Surgery: How Do We Get to Autonomous Actions in Surgery?

Sensors (Basel, Switzerland)
Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intel...