AIMC Topic: Diagnosis, Computer-Assisted

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Multimodal fusion architectures for Alzheimer's disease diagnosis: An experimental study.

Journal of biomedical informatics
OBJECTIVE: In the attempt of early diagnosis of Alzheimer's Disease, varying forms of medical records of multiple modalities are gathered to seize the interaction of multiple factors. However, the heterogeneity of multimodal data brings a challenge. ...

Artificial intelligence medical image-aided diagnosis system for risk assessment of adjacent segment degeneration after lumbar fusion surgery.

SLAS technology
The existing assessment of adjacent segment degeneration (ASD) risk after lumbar fusion surgery focuses on a single type of clinical information or imaging manifestations. In the early stages, it is difficult to show obvious degeneration characterist...

A stacked ensemble approach for symptom-based monkeypox diagnosis.

Computers in biology and medicine
The recent monkeypox outbreak has raised global health concerns. Caused by a virus, it is characterized by symptoms such as skin lesions. Early detection is critical for treatment and controlling its spread. This study uses advanced machine learning ...

Self-supervised multi-modality learning for multi-label skin lesion classification.

Computer methods and programs in biomedicine
BACKGROUND: The clinical diagnosis of skin lesions involves the analysis of dermoscopic and clinical modalities. Dermoscopic images provide detailed views of surface structures, while clinical images offer complementary macroscopic information. Clini...

Combating Medical Label Noise through more precise partition-correction and progressive hard-enhanced learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computer-aided diagnosis systems based on deep neural networks heavily rely on datasets with high-quality labels. However, manual annotation for lesion diagnosis relies on image features, often requiring professional experie...

Use of computer-assisted detection (CADe) colonoscopy in colorectal cancer screening and surveillance: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement.

Endoscopy
This statement conveys the European Society of Gastrointestinal Endoscopy (ESGE) position on the use of computer-aided detection (CADe) with artificial intelligence (AI) during colonoscopy for colorectal cancer (CRC) screening or surveillance. The ES...

Deep learning-based CAD system for Alzheimer's diagnosis using deep downsized KPLS.

Scientific reports
Alzheimer's disease (AD) is the most prevalent type of dementia. It is linked with a gradual decline in various brain functions, such as memory. Many research efforts are now directed toward non-invasive procedures for early diagnosis because early d...

Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches.

European journal of medical research
The rapid advancement of Machine Learning (ML) and Deep Learning (DL) technologies has revolutionized healthcare, particularly in the domains of disease prediction and diagnosis. This study provides a comprehensive review of ML and DL applications ac...

Bio inspired optimization techniques for disease detection in deep learning systems.

Scientific reports
Numerous contemporary computer-aided disease detection methodologies predominantly depend on feature engineering techniques; yet, they possess several drawbacks, including the presence of redundant features and excessive time consumption. Conventiona...

Optimized deep residual networks for early detection of myocardial infarction from ECG signals.

BMC cardiovascular disorders
Globally, the high number of deaths are happening due to Myocardial infarction (MI). MI is considered as a life-threatening disease, which leads to an increase number of deaths or damage to the heart, and hence, prompt detection of MI is critical to ...