AIMC Topic: Humans

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Predicting Reduction Mammaplasty Total Resection Weight With Machine Learning.

Annals of plastic surgery
BACKGROUND: Machine learning (ML) is a form of artificial intelligence that has been used to create better predictive models in medicine. Using ML algorithms, we sought to create a predictive model for breast resection weight based on anthropometric ...

Feasibility study of ResNet-50 in the distinction of intraoral neural tumors using histopathological images.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
BACKGROUND: Neural tumors are difficult to distinguish based solely on cellularity and often require immunohistochemical staining to aid in identifying the cell lineage. This article investigates the potential of a Convolutional Neural Network for th...

Artificial Intelligence in the Provision of Health Care: An American College of Physicians Policy Position Paper.

Annals of internal medicine
Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and health care systems are even developing their own AI models, both within an...

Assessment of Saudi Public Perceptions and Opinions towards Artificial Intelligence in Health Care.

Medicina (Kaunas, Lithuania)
The healthcare system in Saudi Arabia is growing rapidly with the utilization of advanced technologies. Therefore, this study aimed to assess the Saudi public perceptions and opinions towards artificial intelligence (AI) in health care. This cross-...

Comparison of Machine Learning Algorithms Fed with Mobility-Related and Baropodometric Measurements to Identify Temporomandibular Disorders.

Sensors (Basel, Switzerland)
Temporomandibular disorders (TMDs) refer to a group of conditions that affect the temporomandibular joint, causing pain and dysfunction in the jaw joint and related muscles. The diagnosis of TMDs typically involves clinical assessment through operato...

Dual Stream Long Short-Term Memory Feature Fusion Classifier for Surface Electromyography Gesture Recognition.

Sensors (Basel, Switzerland)
Gesture recognition using electromyography (EMG) signals has prevailed recently in the field of human-computer interactions for controlling intelligent prosthetics. Currently, machine learning and deep learning are the two most commonly employed meth...

Enhancing IoT Healthcare with Federated Learning and Variational Autoencoder.

Sensors (Basel, Switzerland)
The growth of IoT healthcare is aimed at providing efficient services to patients by utilizing data from local hospitals. However, privacy concerns can impede data sharing among third parties. Federated learning offers a solution by enabling the trai...

Pleiotropic Effects of Direct Oral Anticoagulants in Chronic Heart Failure and Atrial Fibrillation: Machine Learning Analysis.

Molecules (Basel, Switzerland)
Oral anticoagulant therapy (OAT) for managing atrial fibrillation (AF) encompasses vitamin K antagonists (VKAs, such as warfarin), which was the mainstay of anticoagulation therapy before 2010, and direct-acting oral anticoagulants (DOACs, namely dab...

TumFlow: An AI Model for Predicting New Anticancer Molecules.

International journal of molecular sciences
Melanoma is the fifth most common cancer in the United States. Conventional drug discovery methods are inherently time-consuming and costly, which imposes significant limitations. However, the advent of Artificial Intelligence (AI) has opened up new ...