AIMC Topic: Diagnosis, Computer-Assisted

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Cardiovascular disease diagnosis using cross-domain transfer learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While cardiovascular diseases (CVDs) are commonly diagnosed by cardiologists via inspecting electrocardiogram (ECG) waveforms, these decisions can be supported by a data-driven approach, which may automate this process. An automatic diagnostic approa...

Myocardial Infarction Detection Based on Multi-lead Ensemble Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic myocardial infarction (MI) detection using an electrocardiogram (ECG) is of great significance for improving the survival rate of patients. In this study, we propose a multi-lead ensemble neural network (MENN) to distinguish anterior myocar...

Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The lethal nature of pancreatic ductal adenocarcinoma (PDAC) calls for early differential diagnosis of pancreatic cysts, which are identified in up to 16% of normal subjects, and some of them may develop into PDAC. Pancreatic cysts have a large varia...

Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aided diagnosis (CAD) systems have been developed for decades and have employed either conventional handcrafted features or modern automatic deep-learned...

Hybrid Unified Deep Learning Network for Highly Precise Gleason Grading of Prostate Cancer.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Prostate cancer is one of the leading causes of death around the world. The manual Gleason grading of prostate cancer after histological analysis of stained tissue slides is rigorous, time-consuming and also suffers from subjectivity among experts. I...

[Recent Developments in a Automated Diagnosis of Pathological Images and Three-dimensional Histopathology].

Brain and nerve = Shinkei kenkyu no shinpo
Rapid improvements in computing power are advancing machine learning technology using neural networks, revolutionizing the field of image analysis and allowing for automated diagnosis of pathological images. In addition, the recent development of tis...

Artificial intelligence in diabetic retinopathy: A natural step to the future.

Indian journal of ophthalmology
Use of artificial intelligence in medicine in an evolving technology which holds promise for mass screening and perhaps may even help in establishing an accurate diagnosis. The ability of complex computing is to perform pattern recognition by creatin...

Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach.

Mathematical biosciences and engineering : MBE
Obstructive sleep apnea (OSA) is a common sleep-related respiratory disease that affects people's health, especially in the elderly. In the traditional PSG-based OSA detection, people's sleep may be disturbed, meanwhile the electrode slices are easil...

Impact of Data Presentation on Physician Performance Utilizing Artificial Intelligence-Based Computer-Aided Diagnosis and Decision Support Systems.

Journal of digital imaging
Ultrasound (US) is a valuable imaging modality used to detect primary breast malignancy. However, radiologists have a limited ability to distinguish between benign and malignant lesions on US, leading to false-positive and false-negative results, whi...