AIMC Topic: Deep Learning

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Deep Learning for Intelligent Assessment of Financial Investment Risk Prediction.

Computational intelligence and neuroscience
Financial investment promotes the market's fast economic growth and gradually becomes a new trend of social development in the contemporary era. From the national level, financial risk investment activities directly affect the development process of ...

Research on the Guidance of Youth Labor Education Based on the "Combination of Education and Production Labor" Program Based on the Deep Learning Model.

Computational intelligence and neuroscience
At present, there is a lack of research on Marx's idea of "combining education and productive labor" and its guiding significance for youth labor education, and no effective teaching model has been formed. In response to this problem, this study prop...

Automatic Detection and Segmentation of Ovarian Cancer Using a Multitask Model in Pelvic CT Images.

Oxidative medicine and cellular longevity
Ovarian cancer is one of the most common malignant tumours of female reproductive organs in the world. The pelvic CT scan is a common examination method used for the screening of ovarian cancer, which shows the advantages in safety, efficiency, and p...

Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm.

European radiology
OBJECTIVES: To evaluate deep neural networks for automatic rib fracture detection on thoracic CT scans and to compare its performance with that of attending-level radiologists using a large amount of datasets from multiple medical institutions.

Fast and scalable search of whole-slide images via self-supervised deep learning.

Nature biomedical engineering
The adoption of digital pathology has enabled the curation of large repositories of gigapixel whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic features within large repositories without requiring supervised trainin...

RadioBERT: A deep learning-based system for medical report generation from chest X-ray images using contextual embeddings.

Journal of biomedical informatics
BACKGROUND: Increasing number of chest X-ray (CXR) examinations in radiodiagnosis departments burdens radiologists' and makes the timely generation of accurate radiological reports highly challenging. An automatic radiological report generation (ARRG...

Deep Learning and 5G and Beyond for Child Drowning Prevention in Swimming Pools.

Sensors (Basel, Switzerland)
Drowning is a major health issue worldwide. The World Health Organization's global report on drowning states that the highest rates of drowning deaths occur among children aged 1-4 years, followed by children aged 5-9 years. Young children can drown ...

Human Monkeypox Classification from Skin Lesion Images with Deep Pre-trained Network using Mobile Application.

Journal of medical systems
Recently, human monkeypox outbreaks have been reported in many countries. According to the reports and studies, quick determination and isolation of infected people are essential to reduce the spread rate. This study presents an Android mobile applic...

Identification of micro- and nanoplastics released from medical masks using hyperspectral imaging and deep learning.

The Analyst
Apart from other severe consequences, the COVID-19 pandemic has inflicted a surge in personal protective equipment usage, some of which, such as medical masks, have a short effective protection time. Their misdisposition and subsequent natural degrad...

Classification of Multiclass Histopathological Breast Images Using Residual Deep Learning.

Computational intelligence and neuroscience
Pathologists need a lot of clinical experience and time to do the histopathological investigation. AI may play a significant role in supporting pathologists and resulting in more accurate and efficient histopathological diagnoses. Breast cancer is on...