AIMC Topic: Diagnosis, Computer-Assisted

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Improved pulmonary embolism detection in CT pulmonary angiogram scans with hybrid vision transformers and deep learning techniques.

Scientific reports
Pulmonary embolism (PE) represents a severe, life-threatening cardiovascular condition and is notably the third leading cause of cardiovascular mortality, after myocardial infarction and stroke. This pathology occurs when blood clots obstruct the pul...

NLSTseg: A Pixel-level Lung Cancer Dataset Based on NLST LDCT Images.

Scientific data
Low-dose computed tomography (LDCT) is the most effective tools for early detection of lung cancer. With advancements in artificial intelligence, various Computer-Aided Diagnosis (CAD) systems are now supported in clinical practice. For radiologists ...

Enhancing B-mode-based breast cancer diagnosis via cross-attention fusion of H-scan and Nakagami imaging with multi-CAM-QUS-Driven XAI.

Physics in medicine and biology
B-mode ultrasound is widely employed for breast lesion diagnosis due to its affordability, widespread availability, and effectiveness, particularly in cases of dense breast tissue where mammography may be less sensitive. However, it disregards critic...

A lightweight YOLOv8-based model for gastric cancer detection.

Computers in biology and medicine
Recent research on deep learning-based gastric cancer detection has demonstrated high performance, with capabilities comparable to or exceeding those of medical professionals. However, the performance of deep learning models depends on the performanc...

A RF-based end-to-end Breast Cancer Prediction algorithm.

Computers in biology and medicine
Breast cancer became the primary cause of cancer-related deaths among women year by year. Early detection and accurate prediction of breast cancer play a crucial role in strengthening the quality of human life. Many scientists have concentrated on an...

WSDC-ViT: a novel transformer network for pneumonia image classification based on windows scalable attention and dynamic rectified linear unit convolutional modules.

Scientific reports
Accurate differential diagnosis of pneumonia remains a challenging task, as different types of pneumonia require distinct treatment strategies. Early and precise diagnosis is crucial for minimizing the risk of misdiagnosis and for effectively guiding...

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 ...

A review on computer-aided diagnostic system to classify the disorders of the gastrointestinal tract.

European journal of medical research
Various diseases, such as colon cancer, gastric cancer, celiac, and bleeding, pose a significant risk to the gastrointestinal (GI) tract, which serves as a fundamental component of the human body. It is less invasive to observe the inner part for dis...

Deep multi-task learning framework for gastrointestinal lesion-aided diagnosis and severity estimation.

Scientific reports
Accurate diagnosis and severity estimation of gastrointestinal tract (GT) lesions are crucial for patient care and effective treatment plan decisions. Traditional methods for diagnosing lesions face challenges in accurately estimating severity due to...

Applications of machine learning for peripheral artery disease diagnosis and management: A systematic review.

Computers in biology and medicine
Peripheral artery disease (PAD) is a chronic condition caused by atherosclerosis, leading to arterial narrowing and obstruction, primarily in the lower extremities. This results in reduced blood flow and increases the risk of loss of limbs and mortal...