AIMC Topic: Diagnosis, Computer-Assisted

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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...

Effectiveness of machine learning models in diagnosis of heart disease: a comparative study.

Scientific reports
The precise diagnosis of heart disease represents a significant obstacle within the medical field, demanding the implementation of advanced diagnostic instruments and methodologies. This article conducts an extensive examination of the efficacy of di...

A novel neuroimaging based early detection framework for alzheimer disease using deep learning.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive function, posing a major global health challenge. Despite its rising prevalence, particularly in low and middle-income countries, early diagnosi...

CareAssist GPT improves patient user experience with a patient centered approach to computer aided diagnosis.

Scientific reports
The rapid integration of artificial intelligence (AI) into healthcare has enhanced diagnostic accuracy; however, patient engagement and satisfaction remain significant challenges that hinder the widespread acceptance and effectiveness of AI-driven cl...

Developing an innovative lung cancer detection model for accurate diagnosis in AI healthcare systems.

Scientific reports
Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. In this study, we proposed a Deep learning techniques-based integr...

Leveraging an ensemble of EfficientNetV1 and EfficientNetV2 models for classification and interpretation of breast cancer histopathology images.

Scientific reports
Breast cancer is the second leading cause of cancer-related deaths among women, following lung cancer, as of 2024. Conventional cancer diagnosis relies on the manual examination of biopsied tissues by pathologists, a time-consuming process that may v...

Hybrid transfer learning and self-attention framework for robust MRI-based brain tumor classification.

Scientific reports
Brain tumors are a significant contributor to cancer-related deaths worldwide. Accurate and prompt detection is crucial to reduce mortality rates and improve patient survival prospects. Magnetic Resonance Imaging (MRI) is crucial for diagnosis, but m...