AIMC Topic: Thermography

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AI-Powered Thermography for Diabetic Foot Risk Stratification: Multicenter Cross-Sectional Study.

JMIR formative research
BACKGROUND: Diabetic foot complications are among the most severe and costly outcomes associated with diabetes, with high prevalence particularly in the Middle East and North Africa region. Current screening tools are often limited by subjectivity, i...

Combined effect of salt stress and high light in plants: from basic statistical approach to machine learning methods.

BMC plant biology
Infrared thermal imaging offers a rapid and sensitive approach to assessing temperature changes in plants caused by salt stress, even in the early stages of exposure. Given the increasing prevalence of salt contamination in the environment, it is ess...

Exploring Women's Perceptions of Traditional Mammography and the Concept of AI-Driven Thermography to Improve the Breast Cancer Screening Journey: Mixed Methods Study.

JMIR cancer
BACKGROUND: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, rad...

Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection.

Scientific reports
Breast cancer is a relatively common carcinoma among women worldwide and remains a considerable public health concern. Consequently, the prompt identification of cancer is crucial, as research indicates that 96% of cancers are treatable if diagnosed ...

Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization.

Scientific reports
Breast cancer remains the most prevalent cause of cancer-related mortality among women worldwide, with an estimated incidence exceeding 500,000 new cases annually. Timely diagnosis is vital for enhancing therapeutic outcomes and increasing survival p...

A hybrid GAN-based deep learning framework for thermogram-based breast cancer detection.

Scientific reports
Breast cancer remains one of the most prevalent and life-threatening diseases among women worldwide, necessitating early and accurate detection methods. Traditional diagnostic approaches often face limitations in sensitivity and specificity, highligh...

Artificial intelligence-based Raynaud's quantification index (ARTIX): an objective mobile-based tool for patient-centered assessment of Raynaud's phenomenon.

Arthritis research & therapy
BACKGROUND: We aimed to develop an artificial intelligence algorithm able to assess Raynaud's phenomenon (RP) from mobile phone photography, ensuring as a patient-centered, image-based method for RP quantification.

Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms.

PloS one
Breast cancer is a significant health issue for women, characterized by its high rates of mortality and sickness. However, its early detection is crucial for improving patient outcomes. Thermography, which measures temperature variations between heal...

Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images.

Scientific reports
The most dangerous form of cancer is breast cancer. This disease is life-threatening because of its aggressive nature and high death rates. Therefore, early discovery increases the patient's survival. Mammography has recently been recommended as diag...

Infrared thermography of beef carcasses and random forest algorithm to predict temperature and pH of Longissimus thoracis on carcasses.

Meat science
This study aimed to evaluate the use of infrared thermography (IRT) as a method for predicting the initial and ultimate temperature, as well as the pH, of the Longissimus thoracis in beef carcasses (LTBC). A total of 102 beef carcasses, consisting of...