AIMC Topic: Diagnosis, Computer-Assisted

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Deep Learning in Microscopy Image Analysis: A Survey.

IEEE transactions on neural networks and learning systems
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a l...

An EEG-based functional connectivity measure for automatic detection of alcohol use disorder.

Artificial intelligence in medicine
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and m...

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

Biomedical engineering online
BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of...

Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms.

Physics in medicine and biology
Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the 'knowledge' learned from non-medical imag...

Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

Translational research : the journal of laboratory and clinical medicine
Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide br...

Artificial Intelligence in Medical Practice: The Question to the Answer?

The American journal of medicine
Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice rem...

Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.

Journal of medical Internet research
BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word emb...

Development of a Reinforcement Learning-based Evolutionary Fuzzy Rule-Based System for diabetes diagnosis.

Computers in biology and medicine
The early diagnosis of disease is critical to preventing the occurrence of severe complications. Diabetes is a serious health problem. A variety of methods have been developed for diagnosing diabetes. The majority of these methods have been developed...

Pronation and supination analysis based on biomechanical signals from Parkinson's disease patients.

Artificial intelligence in medicine
In this work, a fuzzy inference model to evaluate hands pronation/supination exercises during the MDS-UPDRS motor examination is proposed to analyze different extracted features from the bio-mechanical signals acquired from patients with Parkinson's ...