AIMC Topic: Machine Learning

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Screening mitochondria-related biomarkers in skin and plasma of atopic dermatitis patients by bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: There is a significant imbalance of mitochondrial activity and oxidative stress (OS) status in patients with atopic dermatitis (AD). This study aims to screen skin and peripheral mitochondria-related biomarkers, providing insights into th...

Machine learning to predict the occurrence of thyroid nodules: towards a quantitative approach for judicious utilization of thyroid ultrasonography.

Frontiers in endocrinology
INTRODUCTION: Ultrasound is instrumental in the early detection of thyroid nodules, which is crucial for appropriate management and favorable outcomes. However, there is a lack of clinical guidelines for the judicious use of thyroid ultrasonography i...

Air pollution and mortality for cancer of the respiratory system in Italy: an explainable artificial intelligence approach.

Frontiers in public health
Respiratory system cancer, encompassing lung, trachea and bronchus cancer, constitute a substantial and evolving public health challenge. Since pollution plays a prominent cause in the development of this disease, identifying which substances are mos...

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.

Biological psychiatry
Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better un...

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial.

Clinical pharmacology and therapeutics
Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to high-interindividual differences in effective dosage and the narrow therapeutic window. Model-informed precision dosing (MIPD) using machine learning...

A Multi-view Molecular Pre-training with Generative Contrastive Learning.

Interdisciplinary sciences, computational life sciences
Molecular representation learning can preserve meaningful molecular structures as embedding vectors, which is a necessary prerequisite for molecular property prediction. Yet, learning how to accurately represent molecules remains challenging. Previou...

Multi-scale relational graph convolutional network for multiple instance learning in histopathology images.

Medical image analysis
Graph convolutional neural networks have shown significant potential in natural and histopathology images. However, their use has only been studied in a single magnification or multi-magnification with either homogeneous graphs or only different node...

Neural critic learning with accelerated value iteration for nonlinear model predictive control.

Neural networks : the official journal of the International Neural Network Society
In practical industrial processes, the receding optimization solution of nonlinear model predictive control (NMPC) is always a very knotty problem. Based on adaptive dynamic programming, the accelerated value iteration predictive control (AVI-PC) alg...

Validation of a natural language processing algorithm using national reporting data to improve identification of anesthesia-related ADVerse evENTs: The "ADVENTURE" study.

Anaesthesia, critical care & pain medicine
BACKGROUND: Reporting and analysis of adverse events (AE) is associated with improved health system learning, quality outcomes, and patient safety. Manual text analysis is time-consuming, costly, and prone to human errors. We aimed to demonstrate the...

Machine learning model for prediction of permanent stoma after anterior resection of rectal cancer: A multicenter study.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: The conversion from a temporary to a permanent stoma (PS) following rectal cancer surgery significantly impacts the quality of life of patients. However, there is currently a lack of practical preoperative tools to predict PS formation. T...