AIMC Topic: Diagnosis, Computer-Assisted

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A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

Medical physics
BACKGROUND: Deep learning methods for radiomics/computer-aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing.

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Journal of healthcare engineering
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...

Efficient and robust cell detection: A structured regression approach.

Medical image analysis
Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnosis (CAD). It remains a challenging task due to touching cells, inhomogeneous background noise, and l...

Multi-label classification methods for improving comorbidities identification.

Computers in biology and medicine
The medical diagnostic process may be supported by computational classification techniques. In many cases, patients are affected by multiple illnesses, and more than one classification label is required to improve medical decision-making. In this pap...

Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization.

Journal of healthcare engineering
With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and t...

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

Medical image analysis
Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and the...

Artificial intelligence in healthcare: past, present and future.

Stroke and vascular neurology
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI ...