AIMC Topic: Diagnosis, Computer-Assisted

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Retinal vessel segmentation in colour fundus images using Extreme Learning Machine.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Attributes of the retinal vessel play important role in systemic conditions and ophthalmic diagnosis. In this paper, a supervised method based on Extreme Learning Machine (ELM) is proposed to segment retinal vessel. Firstly, a set of 39-D discriminat...

Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

Computers in biology and medicine
Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains...

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.

Scientific reports
Pathologists face a substantial increase in workload and complexity of histopathologic cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic protocols have to focus equally on efficiency and accuracy. In this paper we int...

A General Fuzzy Cerebellar Model Neural Network Multidimensional Classifier Using Intuitionistic Fuzzy Sets for Medical Identification.

Computational intelligence and neuroscience
The diversity of medical factors makes the analysis and judgment of uncertainty one of the challenges of medical diagnosis. A well-designed classification and judgment system for medical uncertainty can increase the rate of correct medical diagnosis....

Collective intelligence in medical diagnosis systems: A case study.

Computers in biology and medicine
Diagnosing a patient's condition is one of the most important and challenging tasks in medicine. We present a study of the application of collective intelligence in medical diagnosis by applying consensus methods. We compared the accuracy obtained wi...

Detecting borderline infection in an automated monitoring system for healthcare-associated infection using fuzzy logic.

Artificial intelligence in medicine
BACKGROUND: Many electronic infection detection systems employ dichotomous classification methods, classifying patient data as pathological or normal with respect to one or several types of infection. An electronic monitoring and surveillance system ...

Respiratory Artefact Removal in Forced Oscillation Measurements: A Machine Learning Approach.

IEEE transactions on bio-medical engineering
GOAL: Respiratory artefact removal for the forced oscillation technique can be treated as an anomaly detection problem. Manual removal is currently considered the gold standard, but this approach is laborious and subjective. Most existing automated t...

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

Scientific reports
This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results...