AIMC Topic: Humans

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Artificial intelligence in retinal imaging: current status and future prospects.

Expert review of medical devices
INTRODUCTION: The steadily growing and aging world population, in conjunction with continuously increasing prevalences of vision-threatening retinal diseases, is placing an increasing burden on the global healthcare system. The main challenges within...

Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.

Molecular biotechnology
Synthetic antibodies (Abs) represent a category of engineered proteins meticulously crafted to replicate the functions of their natural counterparts. Such Abs are generated in vitro, enabling advanced molecular alterations associated with antigen rec...

Automated detection and classification of the rotator cuff tear on plain shoulder radiograph using deep learning.

Journal of shoulder and elbow surgery
BACKGROUND: The diagnosis of rotator cuff tears (RCTs) using radiographs alone is clinically challenging; thus, the utility of deep learning algorithms based on convolutional neural networks has been remarkable in the field of medical imaging recogni...

Large Language Models and Healthcare Alliance: Potential and Challenges of Two Representative Use Cases.

Annals of biomedical engineering
Large language models (LLMS) emerge as the most promising Natural Language Processing approach for clinical practice acceleration (i.e., diagnosis, prevention and treatment procedures). Similarly, intelligent conversational systems that leverage LLMS...

Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to establish a combined method of radiomics and deep learning (DL) in magnetic resonance imaging (MRI) to predict lymph node metastasis (LNM) preoperatively in patients with squamous cell carcinoma of the tongue.

Artificial Intelligence-based quantitative evaluation of retinal vascular parameters in thyroid-associated ophthalmopathy.

Endocrine
PURPOSE: Thyroid-associated ophthalmopathy (TAO) may result in increased metabolism and abnormalities in microcirculation. The fractal dimension (Df) of retinal vessels has been shown to be related to the pathology of a number of ophthalmic disorders...

Role of the artificial intelligence in the management of T1 colorectal cancer.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph node metastasis, necessitating surgical intervention with lymph node dissection. The ability to identify T1b (submucosal invasion depth ≥ 1000 µm) as a...

Predicting Homelessness Among Transitioning U.S. Army Soldiers.

American journal of preventive medicine
INTRODUCTION: This study develops a practical method to triage Army transitioning service members (TSMs) at highest risk of homelessness to target a preventive intervention.

The Promise of Artificial Intelligence-Assisted Point-of-Care Ultrasonography in Perioperative Care.

Journal of cardiothoracic and vascular anesthesia
The role of point-of-care ultrasonography in the perioperative setting has expanded rapidly over recent years. Revolutionizing this technology further is integrating artificial intelligence to assist clinicians in optimizing images, identifying anoma...

Quantifying the calcification of abdominal aorta and major side branches with deep learning.

Clinical radiology
AIM: To explore the possibility of a neural network-based method for quantifying calcifications of the abdominal aorta and its branches.