AIMC Topic: Humans

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An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.

Asian journal of psychiatry
BACKGROUND: Individuals with anxious-depressed (AD) symptoms have more severe mood disorders and cognitive impairment than those with non-anxious depression (NAD) symptoms. Therefore, it is important to clarify the underlying neurophysiology of these...

Revisiting medical image retrieval via knowledge consolidation.

Medical image analysis
As artificial intelligence and digital medicine increasingly permeate healthcare systems, robust governance frameworks are essential to ensure ethical, secure, and effective implementation. In this context, medical image retrieval becomes a critical ...

CLIP in medical imaging: A survey.

Medical image analysis
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising results across various tasks due to its generalizability and interpretabil...

A lightweight PCT-Net for segmenting neural fibers in low-quality CCM images.

Computers in biology and medicine
In this paper, we propose a lightweight Position Channel Transformer Network (PCT-Net) for segmenting slender neural fibers in low-quality corneal confocal microscopy images with speckle noise and uneven lighting. Three modules including the channel ...

Infection and Inflammation in Nuclear Medicine Imaging: The Role of Artificial Intelligence.

Seminars in nuclear medicine
Infectious and inflammatory diseases represent a global challenge. Delayed diagnosis and treatment lead to death, disabilities and impairment of the quality of life. The detection of low-grade inflammation and occult infections remains challenging. N...

Pan-cancer analysis of CDC7 in human tumors: Integrative multi-omics insights and discovery of novel marine-based inhibitors through machine learning and computational approaches.

Computers in biology and medicine
Cancer remains a significant global health challenge, with the Cell Division Cycle 7 (CDC7) protein emerging as a potential therapeutic target due to its critical role in tumor proliferation, survival, and resistance. However, a comprehensive analysi...

Enhancing interdisciplinary image segmentation through a Gaussian-based modified local consensus spatial fuzzy approach.

Computers in biology and medicine
This study aims to introduce a generic fuzzy-based approach tailored explicitly for classifying images originating from an array of diverse sources, having varying degrees of spectral and spatial resolutions, inhomogeneity, artifacts, and entirely di...

Artificial intelligence versus orthopedic surgeons as an orthopedic consultant in the emergency department.

Injury
INTRODUCTION: ChatGPT, a widely accessible AI program, has demonstrated potential in various healthcare applications, including emergency department (ED) triage, differential diagnosis, and patient education. However, its potential in providing recom...

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

EBioMedicine
BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology an...

Real-Time Monitoring of Personal Protective Equipment Adherence Using On-Device Artificial Intelligence Models.

Sensors (Basel, Switzerland)
Personal protective equipment (PPE) is crucial for infection prevention and is effective only when worn correctly and consistently. Health organizations often use education or inspections to mitigate non-compliance, but these are costly and have limi...