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[Deep learning algorithms for intelligent construction of a three-dimensional maxillofacial symmetry reference plane].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
OBJECTIVE: To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data, by utilizing a dynamic graph-based registration network model (maxillofacial dynam...

[An experimental study on distal locking of femoral intramedullary nail assisted by an intelligent orthopedic robot].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery
OBJECTIVE: To explore the advantages and effectiveness of the independently developed intelligent orthopedic robot-assisted distal locking of femoral intramedullary nails.

Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions.

Human brain mapping
While the use of naturalistic stimuli such as movie clips for understanding individual differences and brain-behaviour relationships attracts increasing interest, the influence of stimulus selection remains largely unclear. By using machine learning ...

Application of artificial intelligence in the detection of Borrmann type 4 advanced gastric cancer in upper endoscopy (with video).

Cancer
BACKGROUND: Borrmann type-4 (B-4) advanced gastric cancer is challenging to diagnose through routine endoscopy, leading to a poor prognosis. The objective of this study was to develop an artificial intelligence (AI)-based system capable of detecting ...

Extended Technical and Clinical Validation of Deep Learning-Based Brainstem Segmentation for Application in Neurodegenerative Diseases.

Human brain mapping
Disorders of the central nervous system, including neurodegenerative diseases, frequently affect the brainstem and can present with focal atrophy. This study aimed to (1) optimize deep learning-based brainstem segmentation for a wide range of patholo...

Evaluation of risk factors for thromboembolic events in multiple myeloma patients using multiple machine learning models.

Medicine
Venous thromboembolic events (VTE) is a frequent complication in multiple myeloma (MM) patients, raising mortality. This study aims to use machine learning to identify VTE risk factors in MM, helping to pinpoint high-risk individuals for better clini...

Detection and classification of glomerular lesions in kidney graft biopsies using 2-stage deep learning approach.

Medicine
Acute allograft rejection in patients undergoing renal transplantation is diagnosed through histopathological analysis of renal graft biopsies, which can be used to quantify elementary lesions. However, quantification of elementary lesions requires c...

Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome.

Journal of leukocyte biology
Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk and enhance clinical management. Optimal efficacy of COVID-19 antiviral medications relies on early a...

[Prediction of depression symptoms in seniors and analysis of influencing factors based on explainable machine learning].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
This study aims to construct a machine learning model to predict depression symptoms in the elderly and analyze the key influencing factors of depression in the elderly using the shapley additive interpretation (SHAP) method. Based on entries from ...

Mortality risk assessment using deep learning-based frequency analysis of electroencephalography and electrooculography in sleep.

Sleep
STUDY OBJECTIVES: To assess whether the frequency content of electroencephalography (EEG) and electrooculography (EOG) during nocturnal polysomnography (PSG) can predict all-cause mortality.