AIMC Topic: Humans

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A visual-language foundation model for computational pathology.

Nature medicine
The accelerated adoption of digital pathology and advances in deep learning have enabled the development of robust models for various pathology tasks across a diverse array of diseases and patient cohorts. However, model training is often difficult d...

Heterogeneity and predictors of the effects of AI assistance on radiologists.

Nature medicine
The integration of artificial intelligence (AI) in medical image interpretation requires effective collaboration between clinicians and AI algorithms. Although previous studies demonstrated the potential of AI assistance in improving overall clinicia...

Enhancing the prediction of symptomatic radiation pneumonitis for locally advanced non-small-cell lung cancer by combining 3D deep learning-derived imaging features with dose-volume metrics: a two-center study.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
OBJECTIVE: This study aims to examine the ability of deep learning (DL)-derived imaging features for the prediction of radiation pneumonitis (RP) in locally advanced non-small-cell lung cancer (LA-NSCLC) patients.

Generative artificial intelligence chatbots may provide appropriate informational responses to common vascular surgery questions by patients.

Vascular
OBJECTIVES: Generative artificial intelligence (AI) has emerged as a promising tool to engage with patients. The objective of this study was to assess the quality of AI responses to common patient questions regarding vascular surgery disease processe...

Technical and functional design considerations for a real-world interpretable AI solution for NIR perfusion analysis (including cancer).

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Near infrared (NIR) analysis of tissue perfusion via indocyanine green fluorescence assessment is performed clinically during surgery for a range of indications. Its usefulness can potentially be further enhanced through the application of interpreta...

Machine learning based endothelial cell image analysis of patients undergoing descemet membrane endothelial keratoplasty surgery.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: In this study, we developed a machine learning approach for postoperative corneal endothelial cell images of patients who underwent Descemet's membrane keratoplasty (DMEK).

Age-related changes in human brain functional connectivity using graph theory and machine learning techniques in resting-state fMRI data.

GeroScience
Aging is the basis of neurodegeneration and dementia that affects each endemic in the body. Normal aging in the brain is associated with progressive slowdown and disruptions in various abilities such as motor ability, cognitive impairment, decreasing...

Deep Learning Model for Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Chest Radiographs.

Journal of imaging informatics in medicine
Bronchopulmonary dysplasia (BPD) is common in preterm infants and may result in pulmonary vascular disease, compromising lung function. This study aimed to employ artificial intelligence (AI) techniques to help physicians accurately diagnose BPD in p...