AIMC Topic: Machine Learning

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FibrAIm - The machine learning approach to identify the early stage of liver fibrosis and steatosis.

International journal of medical informatics Feb 15, 2025
BACKGROUND: Early recognition of steatosis (fatty liver) and fibrosis in liver health is crucial for effectively managing and preventing the possibility of liver dysfunction. Detecting steatosis helps identify individuals at risk of liver-related dis...
Humans Machine Learning Diagnosis, Computer-Assisted Non-alcoholic Fatty Liver Disease Fatty Liver Liver Cirrhosis
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Towards clinical prediction with transparency: An explainable AI approach to survival modelling in residential aged care.

Computer methods and programs in biomedicine Feb 15, 2025
BACKGROUND AND OBJECTIVE: Scalable, flexible and highly interpretable tools for predicting mortality in residential aged care facilities for the purpose of informing and optimizing palliative care decisions, do not exist. This study is the first and ...
Humans Male Survival Analysis Palliative Care Proportional Hazards Models Homes for the Aged Artificial Intelligence Female Machine Learning Aged Algorithms Aged, 80 and over
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Coupling analysis of diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) with abnormal cerebral blood flow in methamphetamine-dependent patients and its application in machine-learning-based classification.

Journal of affective disorders Feb 15, 2025
BACKGROUND: Diffusion tensor imaging (DTI) analysis along the perivascular space (ALPS) index is currently widely employed to evaluate the neurophysiological activity in various neuropsychiatric disorders. However, there remains a scarcity of studies...
Adult Male Middle Aged Machine Learning Brain Female Diffusion Tensor Imaging Glymphatic System Methamphetamine Amphetamine-Related Disorders Cerebrovascular Circulation Humans
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Breaking barriers: noninvasive AI model for BRAF mutation identification.

International journal of computer assisted radiology and surgery Feb 15, 2025
OBJECTIVE: BRAF is the most common mutation found in thyroid cancer and is particularly associated with papillary thyroid carcinoma (PTC). Currently, genetic mutation detection relies on invasive procedures. This study aimed to extract radiomic featu...
Humans Artificial Intelligence Deep Learning Thyroid Neoplasms Ultrasonography Sensitivity and Specificity Machine Learning Mutation Proto-Oncogene Proteins B-raf Male Female Thyroid Cancer, Papillary Middle Aged Adult
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Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.

European journal of radiology Feb 15, 2025
PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines. Chest contrast-enhanced computed tomography (CECT) is crucial in the ...
Radiologists Radiographic Image Interpretation, Computer-Assisted Hypertension, Pulmonary Humans Sensitivity and Specificity Machine Learning Male Female Middle Aged Reproducibility of Results Algorithms Retrospective Studies Aged Tomography, X-Ray Computed Adult
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Utilization of machine learning algorithm in the prediction of rehospitalization during one-year post traumatic spinal cord injury.

Spinal cord Feb 15, 2025
STUDY DESIGN: Retrospective cohort study.
Female Aged Young Adult Machine Learning Algorithms Humans Retrospective Studies Length of Stay United States Patient Readmission Adult Spinal Cord Injuries Male Middle Aged
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Scale-independent solid fraction prediction in dry granulation process using a gray-box model integrating machine learning model and Johanson model.

International journal of pharmaceutics Feb 15, 2025
We propose a novel approach for predicting the solid fraction after roller compaction processes. It is crucial to predict and control the solid fraction, as it has a significant impact on the product quality. The solid fraction can be theoretically p...
Technology, Pharmaceutical Chemistry, Pharmaceutical Particle Size Powders Drug Compounding Machine Learning Models, Statistical
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Sensory-biased autoencoder enables prediction of texture perception from food rheology.

Food research international (Ottawa, Ont.) Feb 15, 2025
Understanding how the physical properties of food affect sensory perception remains a critical challenge for food design. Here, we present an innovative machine learning strategy to decode the complex relationships between non-Newtonian rheological a...
Male Female Food Humans Taste Young Adult Autoencoder Neural Networks, Computer Rheology Adult Machine Learning
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A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.

Food research international (Ottawa, Ont.) Feb 15, 2025
With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an eme...
Chemometrics Plant Leaves Tea Quality Control Machine Learning Spectroscopy, Near-Infrared
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Use of machine learning models to identify National Institutes of Health-funded cardiac arrest research.

Resuscitation Feb 15, 2025
OBJECTIVE: To compare the performance of three artificial intelligence (AI) classification strategies against manually classified National Institutes of Health (NIH) cardiac arrest (CA) grants, with the goal of developing a publicly available tool to...
Machine Learning Biomedical Research United States Research Support as Topic Heart Arrest National Institutes of Health (U.S.) Humans
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