AIMC Topic: Adult

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Long-Term Rate of Optic Disc Rim Loss in Glaucoma Patients Measured From Optic Disc Photographs With a Deep Neural Network.

Translational vision science & technology
PURPOSE: This study uses deep neural network-generated rim-to-disc area ratio (RADAR) measurements and the disc damage likelihood scale (DDLS) to measure the rate of optic disc rim loss in a large cohort of glaucoma patients.

Streamlined Intraoperative Brain Tumor Classification and Molecular Subtyping in Stereotactic Biopsies Using Stimulated Raman Histology and Deep Learning.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Recent artificial intelligence algorithms aided intraoperative decision-making via stimulated Raman histology (SRH) during craniotomy. This study assesses deep learning algorithms for rapid intraoperative diagnosis from SRH images in small s...

Early identification of patients at risk for iron-deficiency anemia using deep learning techniques.

American journal of clinical pathology
OBJECTIVES: Iron-deficiency anemia (IDA) is a common health problem worldwide, and up to 10% of adult patients with incidental IDA may have gastrointestinal cancer. A diagnosis of IDA can be established through a combination of laboratory tests, but ...

Development and validation of deep learning models for bowel obstruction on plain abdominal radiograph.

The Journal of international medical research
OBJECTIVE: Artificial intelligence (AI) could help medical practitioners in analyzing radiological images to determine the presence and site of bowel obstruction. This retrospective diagnostic study proposed a series of deep learning (DL) models for ...

Hyperspectral imaging facilitating resect-and-discard strategy through artificial intelligence-assisted diagnosis of colorectal polyps: A pilot study.

Cancer medicine
BACKGROUND AND AIMS: The resect-and-discard strategy for colorectal polyps based on accurate optical diagnosis remains challenges. Our aim was to investigate the feasibility of hyperspectral imaging (HSI) for identifying colorectal polyp properties a...

Epidermal renewal during the treatment of atopic dermatitis lesions: A study coupling line-field confocal optical coherence tomography with artificial intelligence quantifications: LC-OCT reveals new biological markers of AD.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
OBJECTIVE: This study explores the application of Line-field Confocal Optical Coherence Tomography (LC-OCT) imaging coupled with artificial intelligence (AI)-based algorithms to investigate atopic dermatitis (AD), a common inflammatory dermatosis.

Automatic segmentation of esophageal cancer, metastatic lymph nodes and their adjacent structures in CTA images based on the UperNet Swin network.

Cancer medicine
OBJECTIVE: To create a deep-learning automatic segmentation model for esophageal cancer (EC), metastatic lymph nodes (MLNs) and their adjacent structures using the UperNet Swin network and computed tomography angiography (CTA) images and to improve t...

An artificial intelligence powered study of enlarged facial pore prevalence on one million Chinese from different age groups and its correlation with environmental factors.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Enlarged pores are amidst one of the top cosmetic concerns, especially among Chinese. Many small-group studies have been conducted in understanding their prevalence and beauty relevance. Nonetheless, population-level investigations are st...

Machine Learning-Driven Phenogrouping and Cardiorespiratory Fitness Response in Metastatic Breast Cancer.

JCO clinical cancer informatics
PURPOSE: The magnitude of cardiorespiratory fitness (CRF) impairment during anticancer treatment and CRF response to aerobic exercise training (AT) are highly variable. The aim of this ancillary analysis was to leverage machine learning approaches to...