AIMC Topic: Deep Learning

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Diagnosis of Osteoporosis using modified U-net architecture with attention unit in DEXA and X-ray images.

Journal of X-ray science and technology
BACKGROUND: Osteoporosis, a silent killing disease of fracture risk, is normally determined based on the bone mineral density (BMD) and T-score values measured in bone. However, development of standard algorithms for accurate segmentation and BMD mea...

Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning.

Journal of X-ray science and technology
OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated dete...

Current Advances and Limitations of Deep Learning in Anticancer Drug Sensitivity Prediction.

Current topics in medicinal chemistry
Anticancer drug screening can accelerate drug discovery to save the lives of cancer patients, but cancer heterogeneity makes this screening challenging. The prediction of anticancer drug sensitivity is useful for anticancer drug development and the i...

Deep learning-based CAD schemes for the detection and classification of lung nodules from CT images: A survey.

Journal of X-ray science and technology
BACKGROUND: Lung cancer is the most common cancer in the world. Computed tomography (CT) is the standard medical imaging modality for early lung nodule detection and diagnosis that improves patient's survival rate. Recently, deep learning algorithms,...

[Present and future perspectives of artificial intelligence: examples of mathematical approaches for analysis of disease dynamics].

[Rinsho ketsueki] The Japanese journal of clinical hematology
Artificial intelligence (AI) has been applied widely in medicine. For example, deep neural network-based deep learning is particularly effective for pattern recognition in static medical images. Additionally, dynamic time series data are analysed ubi...

Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks.

Current medical imaging
BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular h...

Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.

Current medical imaging
BACKGROUND: Automated intelligent systems for unbiased diagnosis are primary requirement for the pigment lesion analysis. It has gained the attention of researchers in the last few decades. These systems involve multiple phases such as pre-processing...

A natural evolution optimization based deep learning algorithm for neurological disorder classification.

Bio-medical materials and engineering
BACKGROUND: A neurological disorder is one of the significant problems of the nervous system that affects the essential functions of the human brain and spinal cord. Monitoring brain activity through electroencephalography (EEG) has become an importa...

A Deep Learning Approach for Human Action Recognition Using Skeletal Information.

Advances in experimental medicine and biology
In this paper we present an approach toward human action detection for activities of daily living (ADLs) that uses a convolutional neural network (CNN). The network is trained on discrete Fourier transform (DFT) images that result from raw sensor rea...