AIMC Topic: Machine Learning

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A Pipeline for the Implementation and Visualization of Explainable Machine Learning for Medical Imaging Using Radiomics Features.

Sensors (Basel, Switzerland)
Machine learning (ML) models have been shown to predict the presence of clinical factors from medical imaging with remarkable accuracy. However, these complex models can be difficult to interpret and are often criticized as "black boxes". Prediction ...

Quantifying information of intracellular signaling: progress with machine learning.

Reports on progress in physics. Physical Society (Great Britain)
Cells convey information about their extracellular environment to their core functional machineries. Studying the capacity of intracellular signaling pathways to transmit information addresses fundamental questions about living systems. Here, we revi...

Cultural and Creative Product Design and Image Recognition Based on Deep Learning.

Computational intelligence and neuroscience
In today's technological world, advanced intelligence technologies such as deep learning (DL) techniques are widely applied in various fields. In this study, people are going to research cultural and creative product design and image recognition base...

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system.

Molecular diversity
CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique c...

Analyzing Transfer Learning of Vision Transformers for Interpreting Chest Radiography.

Journal of digital imaging
Limited availability of medical imaging datasets is a vital limitation when using "data hungry" deep learning to gain performance improvements. Dealing with the issue, transfer learning has become a de facto standard, where a pre-trained convolution ...

Machine Learning Analysis Provides Insight into Mechanisms of Protein Particle Formation Inside Containers During Mechanical Agitation.

Journal of pharmaceutical sciences
Container choice can influence particle generation within protein formulations. Incompatibility between proteins and containers can manifest as increased particle concentrations, shifts in particle size distributions and changes in particle morpholog...

Development of a machine learning model for the prediction of the short-term mortality in patients in the intensive care unit.

Journal of critical care
PURPOSE: The aim of this study was to develop and evaluate a machine learning model that predicts short-term mortality in the intensive care unit using the trends of four easy-to-collect vital signs.

Machine Learning of Coupled Cluster (T)-Energy Corrections via Delta (Δ)-Learning.

Journal of chemical theory and computation
Accurate thermochemistry is essential in many chemical disciplines, such as astro-, atmospheric, or combustion chemistry. These areas often involve fleetingly existent intermediates whose thermochemistry is difficult to assess. Whenever direct calori...

Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach.

BMC medical research methodology
BACKGROUND: The individual data collected throughout patient follow-up constitute crucial information for assessing the risk of a clinical event, and eventually for adapting a therapeutic strategy. Joint models and landmark models have been proposed ...

Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment.

Scientific reports
The Electronic Medical Record (EMR) provides an opportunity to manage patient care efficiently and accurately. This includes clinical decision support tools for the timely identification of adverse events or acute illnesses preceded by deterioration....