AIMC Topic: Diagnosis, Computer-Assisted

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[Application of artificial intelligence in glaucoma. Part 2. Neural networks and machine learning in the monitoring and treatment of glaucoma].

Vestnik oftalmologii
The second part of the literature review on the application of artificial intelligence (AI) methods for screening, diagnosing, monitoring, and treating glaucoma provides information on how AI methods enhance the effectiveness of glaucoma monitoring a...

A Systematic Review on Deep Learning Model in Computer-aided Diagnosis for Anterior Cruciate Ligament Injury.

Current medical imaging
INTRODUCTION: In developing Computer-Aided Diagnosis (CAD), a Convolutional Neural Network (CNN) has been commonly used as a Deep Learning (DL) model. Although it is still early, DL has excellent potential in implementing computers in medical diagnos...

Automatic detection of thyroid nodules with a real-time artificial intelligence system in a real clinical scenario and the associated influencing factors.

Clinical hemorheology and microcirculation
BACKGROUND: At present, most articles mainly focused on the diagnosis of thyroid nodules by using artificial intelligence (AI), and there was little research on the detection performance of AI in thyroid nodules.

Research on breast cancer pathological image classification method based on wavelet transform and YOLOv8.

Journal of X-ray science and technology
 Breast cancer is one of the cancers with high morbidity and mortality in the world, which is a serious threat to the health of women. With the development of deep learning, the recognition about computer-aided diagnosis technology is getting higher ...

Reduction of overfitting on the highly imbalanced ISIC-2019 skin dataset using deep learning frameworks.

Journal of X-ray science and technology
BACKGROUND: With the rapid growth of Deep Neural Networks (DNN) and Computer-Aided Diagnosis (CAD), more significant works have been analysed for cancer related diseases. Skin cancer is the most hazardous type of cancer that cannot be diagnosed in th...

Optimizing Computer-Aided Diagnosis with Cost-Aware Deep Learning Models.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Classical machine learning and deep learning models for Computer-Aided Diagnosis (CAD) commonly focus on overall classification performance, treating misclassification errors (false negatives and false positives) equally during training. This uniform...

Colon Disease Classification Method Based on Deep Learning.

Studies in health technology and informatics
Objective Colorectal cancer (CRC) is a common malignant tumor of the digestive system with a high incidence rate. It is prone to misdiagnosis or missed diagnosis in clinical practice. Therefore, researching computer-aided diagnostic methods for endos...

Artificial intelligence suppression as a strategy to mitigate artificial intelligence automation bias.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Incorporating artificial intelligence (AI) into clinics brings the risk of automation bias, which potentially misleads the clinician's decision-making. The purpose of this study was to propose a potential strategy to mitigate automation b...

Unlocking glioma genetics with deep learning.

Med (New York, N.Y.)
The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of human disease. CHARM, an AI algorithm described in this issue, has the potential to streamline molecular classification, intraoperative diagnosis, surgi...