AIMC Topic: Humans

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[Artificial intelligence and glaucoma: A literature review].

Journal francais d'ophtalmologie
In recent years, research in artificial intelligence (AI) has experienced an unprecedented surge in the field of ophthalmology, in particular glaucoma. The diagnosis and follow-up of glaucoma is complex and relies on a body of clinical evidence and a...

A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for finding emergent or urgent conditions in patients. In an emergency department, automatic detection and...

Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BMC anesthesiology
BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) d...

Screening Anti-inflammatory, Anticoagulant, and Respiratory Agents for SARS-CoV-2 3CL Inhibition from Chemical Fingerprints Through a Deep Learning Approach.

Revista de investigacion clinica; organo del Hospital de Enfermedades de la Nutricion
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), triggers a pathophysiological process linked not only to viral mechanisms of infectivity, but also to the pattern of...

Pruning Growing Self-Organizing Map Network for Human Physical Activity Identification.

Journal of healthcare engineering
Human physical activity identification based on wearable sensors is of great significance to human health analysis. A large number of machine learning models have been applied to human physical activity identification and achieved remarkable results....

Application of Deep Learning in Lung Cancer Imaging Diagnosis.

Journal of healthcare engineering
Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. It poses a great threat to human health and it mainly occurs in smokers. In our country, with the acceleration of industrialization, environmental pol...

Contribution of phosphorus and PTH to the development of cardiac hypertrophy and fibrosis in an experimental model of chronic renal failure.

Nefrologia
BACKGROUND AND OBJECTIVE: Adequate serum phosphorus levels in patients with chronic kidney disease is essential for their clinical management. However, the control of hyperphosphatemia is difficult because is normally associated with increases in ser...

Application of Machine Learning for Cytometry Data.

Frontiers in immunology
Modern cytometry technologies present opportunities to profile the immune system at a single-cell resolution with more than 50 protein markers, and have been widely used in both research and clinical settings. The number of publicly available cytomet...

Predicting miRNA-Disease Association Based on Neural Inductive Matrix Completion with Graph Autoencoders and Self-Attention Mechanism.

Biomolecules
Many studies have clarified that microRNAs (miRNAs) are associated with many human diseases. Therefore, it is essential to predict potential miRNA-disease associations for disease pathogenesis and treatment. Numerous machine learning and deep learnin...

Disease Progression Detection via Deep Sequence Learning of Successive Radiographic Scans.

International journal of environmental research and public health
The highly rapid spread of the current pandemic has quickly overwhelmed hospitals all over the world and motivated extensive research to address a wide range of emerging problems. The unforeseen influx of COVID-19 patients to hospitals has made it in...