AIMC Topic: Machine Learning

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Machine learning (ML) techniques to predict breast cancer in imbalanced datasets: a systematic review.

Journal of cancer survivorship : research and practice
Knowledge discovery in databases (KDD) is crucial in analyzing data to extract valuable insights. In medical outcome prediction, KDD is increasingly applied, particularly in diseases with high incidence, mortality, and costs, like cancer. ML techniqu...

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

Journal of autism and developmental disorders
PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic crite...

DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

Microscopy research and technique
In recent days, non-communicable diseases (NCDs) require more attention since they require specialized infrastructure for treatment. As per the cancer population registry estimate, nearly 800,000 new cancer cases will be detected yearly. The statisti...

Applications and Advances in Machine Learning Force Fields.

Journal of chemical information and modeling
Force fields (FFs) form the basis of molecular simulations and have significant implications in diverse fields such as materials science, chemistry, physics, and biology. A suitable FF is required to accurately describe system properties. However, an...

Revolutionizing Digital Pathology With the Power of Generative Artificial Intelligence and Foundation Models.

Laboratory investigation; a journal of technical methods and pathology
Digital pathology has transformed the traditional pathology practice of analyzing tissue under a microscope into a computer vision workflow. Whole-slide imaging allows pathologists to view and analyze microscopic images on a computer monitor, enablin...

Applying feature selection and machine learning techniques to estimate the biomass higher heating value.

Scientific reports
The biomass higher heating value (HHV) is an important thermal property that determines the amount of recoverable energy from agriculture byproducts. Precise laboratory measurement or accurate prediction of the HHV is essential for designing biomass ...

Is AI essential? Examining the need for deep learning in image-activated sorting of .

Lab on a chip
Artificial intelligence (AI) has become a focal point across a multitude of societal sectors, with science not being an exception. Particularly in the life sciences, imaging flow cytometry has increasingly integrated AI for automated management and c...

A comparison of machine learning methods to find clinical trials for inclusion in new systematic reviews from their PROSPERO registrations prior to searching and screening.

Research synthesis methods
Searching for trials is a key task in systematic reviews and a focus of automation. Previous approaches required knowing examples of relevant trials in advance, and most methods are focused on published trial articles. To complement existing tools, w...

From lazy to rich to exclusive task representations in neural networks and neural codes.

Current opinion in neurobiology
Neural circuits-both in the brain and in "artificial" neural network models-learn to solve a remarkable variety of tasks, and there is a great current opportunity to use neural networks as models for brain function. Key to this endeavor is the abilit...

Opportunities and challenges of 5G network technology toward precision medicine.

Clinical and translational science
Moving away from traditional "one-size-fits-all" treatment to precision-based medicine has tremendously improved disease prognosis, accuracy of diagnosis, disease progression prediction, and targeted-treatment. The current cutting-edge of 5G network ...