AI Medical Compendium Topic

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Diagnosis, Computer-Assisted

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Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects.

Computers in biology and medicine
In recent years, there has been a significant improvement in the accuracy of the classification of pigmented skin lesions using artificial intelligence algorithms. Intelligent analysis and classification systems are significantly superior to visual d...

Diagnostic test accuracy of externally validated convolutional neural network (CNN) artificial intelligence (AI) models for emergency head CT scans - A systematic review.

International journal of medical informatics
BACKGROUND: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided diagnosis (CADx) for emergency...

Curve-Modelling and Machine Learning for a Better COPD Diagnosis.

International journal of chronic obstructive pulmonary disease
BACKGROUND: Development of new tools in artificial intelligence has an outstanding performance in the recognition of multidimensional patterns, which is why they have proven to be useful in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD...

Artificial intelligence-driven computer aided diagnosis system provides similar diagnosis value compared with doctors' evaluation in lung cancer screening.

BMC medical imaging
OBJECTIVE: To evaluate the consistency between doctors and artificial intelligence (AI) software in analysing and diagnosing pulmonary nodules, and assess whether the characteristics of pulmonary nodules derived from the two methods are consistent fo...

New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.

Computers in biology and medicine
BACKGROUND: Efficient and precise diagnosis of non-small cell lung cancer (NSCLC) is quite critical for subsequent targeted therapy and immunotherapy. Since the advent of whole slide images (WSIs), the transition from traditional histopathology to di...

Automatic detection of epilepsy from EEGs using a temporal convolutional network with a self-attention layer.

Biomedical engineering online
BACKGROUND: Over 60% of epilepsy patients globally are children, whose early diagnosis and treatment are critical for their development and can substantially reduce the disease's burden on both families and society. Numerous algorithms for automated ...

Does machine learning have a high performance to predict obesity among adults and older adults? A systematic review and meta-analysis.

Nutrition, metabolism, and cardiovascular diseases : NMCD
AIM: Machine learning may be a tool with the potential for obesity prediction. This study aims to review the literature on the performance of machine learning models in predicting obesity and to quantify the pooled results through a meta-analysis.

Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images.

BMC medical informatics and decision making
BACKGROUND: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm for computer-aided diagnosis...

Light&fast generative adversarial network for high-fidelity CT image synthesis of liver tumor.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma is a common disease with high mortality. Through deep learning methods to analyze HCC CT, the screening classification and prognosis model of HCC can be established, which further promotes the develo...