AIMC Topic: Diagnosis, Computer-Assisted

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A Multi-scale U-Net for Semantic Segmentation of Histological Images from Radical Prostatectomies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Gleason grading of histological images is important in risk assessment and treatment planning for prostate cancer patients. Much research has been done in classifying small homogeneous cancer regions within histological images. However, semi-supervis...

Deep learning for healthcare applications based on physiological signals: A review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.20...

Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks.

The British journal of radiology
Deep learning has demonstrated tremendous revolutionary changes in the computing industry and its effects in radiology and imaging sciences have begun to dramatically change screening paradigms. Specifically, these advances have influenced the develo...

Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...

Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment.

Journal of biomedical informatics
Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, u...

Novel computer algorithm for cough monitoring based on octonions.

Respiratory physiology & neurobiology
The objective assessment of cough frequency is essential for evaluation of cough and antitussive therapies. Nonetheless, available algorithms for automatic detection of cough sound have limited sensitivity and the analysis of cough sound often requir...

Deep learning in mammography and breast histology, an overview and future trends.

Medical image analysis
Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promisin...

Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Computerized detection of voice disorders has attracted considerable academic and clinical interest in the hope of providing an effective screening method for voice diseases before endoscopic confirmation. This study proposes a deep-learn...

A Deep Belief Network and Dempster-Shafer-Based Multiclassifier for the Pathology Stage of Prostate Cancer.

Journal of healthcare engineering
OBJECT: Pathologic prediction of prostate cancer can be made by predicting the patient's prostate metastasis prior to surgery based on biopsy information. Because biopsy variables associated with pathology have uncertainty regarding individual patien...