AIMC Topic: Humans

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Machine learning-based colorectal cancer prediction using global dietary data.

BMC cancer
BACKGROUND: Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Active health screening for CRC yielded detection of an increasingly younger adults. However, current machine learning algorithms that are trained using older ...

Diagnosis of coronary layered plaque by deep learning.

Scientific reports
Healed coronary plaques, morphologically characterized by a layered phenotype, are signs of previous plaque destabilization and healing. Recent optical coherence tomography (OCT) studies demonstrated that layered plaque is associated with higher leve...

Developing a machine learning algorithm to predict probability of retear and functional outcomes in patients undergoing rotator cuff repair surgery: protocol for a retrospective, multicentre study.

BMJ open
INTRODUCTION: The effectiveness of rotator cuff tear repair surgery is influenced by multiple patient-related, pathology-centred and technical factors, which is thought to contribute to the reported retear rates between 17% and 94%. Adequate patient ...

Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.

Journal of medical Internet research
BACKGROUND: Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and follow the epoch.

Deep learning based direct segmentation assisted by deformable image registration for cone-beam CT based auto-segmentation for adaptive radiotherapy.

Physics in medicine and biology
Cone-beam CT (CBCT)-based online adaptive radiotherapy calls for accurate auto-segmentation to reduce the time cost for physicians. However, deep learning (DL)-based direct segmentation of CBCT images is a challenging task, mainly due to the poor ima...

Comparison of the dynamics of exoskeletal-assisted and unassisted locomotion in an FDA-approved lower extremity device: Controlled experiments and development of a subject-specific virtual simulator.

PloS one
Robotic exoskeletons have considerable, but largely untapped, potential to restore mobility in individuals with neurological disorders, and other conditions that result in partial or complete immobilization. The growing demand for these devices neces...

Deep learning applications in osteoarthritis imaging.

Skeletal radiology
Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will provide a review of current applications of DL in osteoarthritis (OA) imaging, including methods used for cartilage lesion detection, OA diagnosis, cartila...

Learning curves and perioperative outcomes of single-incision robotic sacrocolpopexy on two different da Vinci surgical systems.

Journal of robotic surgery
This study aimed to report a single surgeon's early experience and learning curves of single-incision robotic sacrocolpopexy on two different robotic surgical platforms, namely, the single-site approach on da Vinci Xi and single-port approach on da V...

Prediction models for the impact of the COVID-19 pandemic on research activities of Japanese nursing researchers using deep learning.

Japan journal of nursing science : JJNS
AIM: This study aimed to construct and evaluate prediction models using deep learning to explore the impact of attributes and lifestyle factors on research activities of nursing researchers during the COVID-19 pandemic.

Pure robotic major hepatectomy with biliary reconstruction for hepatobiliary malignancies: first European results.

Surgical endoscopy
BACKGROUND: Combined liver and bile duct resection with biliary reconstruction for hepatobiliary malignancies are defined as highly complex surgical procedures. The robotic platform may overcome some major limitations of conventional laparoscopic sur...