AIMC Topic: Humans

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Investigating the role of large language models on questions about refractive surgery.

International journal of medical informatics
BACKGROUND: Large language models (LLMs) are becoming increasingly popular and are playing an important role in providing accurate clinical information to both patients and physicians. This study aimed to investigate the effectiveness of ChatGPT-4.0,...

An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.

Journal of neuroscience methods
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...

Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning.

Radiological physics and technology
Self-supervised learning (SSL) has gained attention in the medical field as a deep learning approach utilizing unlabeled data. The Jigsaw puzzle task in SSL enables models to learn both features of images and the positional relationships within image...

Enhancing percutaneous coronary intervention using TriVOCTNet: a multi-task deep learning model for comprehensive intravascular optical coherence tomography analysis.

Physical and engineering sciences in medicine
Neointimal coverage and stent apposition, as assessed from intravascular optical coherence tomography (IVOCT) images, are crucial for optimizing percutaneous coronary intervention (PCI). Existing state-of-the-art computer algorithms designed to autom...

Artificial intelligence in antimicrobial stewardship: a systematic review and meta-analysis of predictive performance and diagnostic accuracy.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
The increasing threat of antimicrobial resistance has prompted a need for more effective antimicrobial stewardship programs (AMS). Artificial intelligence (AI) and machine learning (ML) tools have emerged as potential solutions to enhance decision-ma...

MSRMMP: Multi-scale residual module and multi-layer pseudo-supervision for weakly supervised segmentation of histopathological images.

Medical engineering & physics
Accurate semantic segmentation of histopathological images plays a crucial role in accurate cancer diagnosis. While fully supervised learning models have shown outstanding performance in this field, the annotation cost is extremely high. Weakly Super...

Machine learning discovery of novel antihypertensive peptides from highland barley protein inhibiting angiotensin I-converting enzyme (ACE).

Food research international (Ottawa, Ont.)
Hypertension is a major global health concern, and there is a need for new antihypertensive agents derived from natural sources. This study aims to identify novel angiotensin I-converting enzyme (ACE) inhibitors from bioactive peptides derived from f...

Clinicians' perspectives on the use of artificial intelligence to triage MRI brain scans.

European journal of radiology
Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and also relieve clinician workload. Validated AI tools can mitigate the delays in reporting scans by flagging time-sensitive and actionable findings. In ...

Artificial intelligence-enhanced navigation for nerve recognition and surgical education in laparoscopic colorectal surgery.

Surgical endoscopy
BACKGROUND: Devices that help educate young doctors and enable safe, minimally invasive surgery are needed. Eureka is a surgical artificial intelligence (AI) system that can intraoperatively highlight loose connective tissues (LCTs) in the dissected ...

An accelerated deep learning model can accurately identify clinically important humeral and scapular landmarks on plain radiographs obtained before and after anatomic arthroplasty.

International orthopaedics
PURPOSE: Accurate identification of radiographic landmarks is fundamental to characterizing glenohumeral relationships before and sequentially after shoulder arthroplasty, but manual annotation of these radiographs is laborious. We report on the use ...