AIMC Topic: Humans

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Short-term outcomes in robot-assisted compared to laparoscopic colon cancer resections: a systematic review and meta-analysis.

Surgical endoscopy
BACKGROUND: Robot-assisted surgery is increasingly adopted in colorectal surgery. However, evidence for the implementation of robot-assisted surgery for colon cancer is sparse. This study aims to evaluate the short-term outcomes of robot-assisted col...

Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018.

Psychiatry research
Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk assessment model is conducive to early detection and early treatment of high-risk groups of depressi...

A novel deep neuroevolution-based image classification method to diagnose coronavirus disease (COVID-19).

Computers in biology and medicine
COVID-19 has had a detrimental impact on normal activities, public safety, and the global financial system. To identify the presence of this disease within communities and to commence the management of infected patients early, positive cases should b...

Neural interface systems with on-device computing: machine learning and neuromorphic architectures.

Current opinion in biotechnology
Development of neural interface and brain-machine interface (BMI) systems enables the treatment of neurological disorders including cognitive, sensory, and motor dysfunctions. While neural interfaces have steadily decreased in form factor, recent dev...

Biomedical Ontologies to Guide AI Development in Radiology.

Journal of digital imaging
The advent of deep learning has engendered renewed and rapidly growing interest in artificial intelligence (AI) in radiology to analyze images, manipulate textual reports, and plan interventions. Applications of deep learning and other AI approaches ...

Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.

Medical physics
PURPOSE: To investigate multiple deep learning methods for automated segmentation (auto-segmentation) of the parotid glands, submandibular glands, and level II and level III lymph nodes on magnetic resonance imaging (MRI). Outlining radiosensitive or...

Study the Effect of the Risk Factors in the Estimation of the Breast Cancer Risk Score Using Machine Learning.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: Early prediction of breast cancer is one of the most essential fields of medicine. Many studies have introduced prediction approaches to facilitate the early prediction and estimate the future occurrence based on mammography periodic tests...

A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

JAMA network open
IMPORTANCE: The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by t...

Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records.

JAMA network open
IMPORTANCE: Detecting cognitive decline earlier among older adults can facilitate enrollment in clinical trials and early interventions. Clinical notes in longitudinal electronic health records (EHRs) provide opportunities to detect cognitive decline...

Evaluation of an Artificial Intelligence-Augmented Digital System for Histologic Classification of Colorectal Polyps.

JAMA network open
IMPORTANCE: Colorectal polyps are common, and their histopathologic classification is used in the planning of follow-up surveillance. Substantial variation has been observed in pathologists' classification of colorectal polyps, and improved assessmen...