AIMC Topic: Deep Learning

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Investigating the Association between Streetscapes and Mental Health in Zhanjiang, China: Using Baidu Street View Images and Deep Learning.

International journal of environmental research and public health
Mental health is one of the main factors that significantly affect one's life. Previous studies suggest that streets are the main activity space for urban residents and have important impacts on human mental health. Existing studies, however, have no...

A multi-scale, multi-region and attention mechanism-based deep learning framework for prediction of grading in hepatocellular carcinoma.

Medical physics
BACKGROUND: Histopathological grading is a significant risk factor for postsurgical recurrence in hepatocellular carcinoma (HCC). Preoperative knowledge of histopathological grading could provide instructive guidance for individualized treatment deci...

Deep-learning-based personalized prediction of absolute neutrophil count recovery and comparison with clinicians for validation.

Journal of biomedical informatics
Neutropenia and its complications are major adverse effects of cytotoxic chemotherapy. The time to recovery from neutropenia varies from patient to patient, and cannot be easily predicted even by experts. Therefore, we trained a deep learning model u...

Real-Time Human Activity Recognition with IMU and Encoder Sensors in Wearable Exoskeleton Robot via Deep Learning Networks.

Sensors (Basel, Switzerland)
Wearable exoskeleton robots have become a promising technology for supporting human motions in multiple tasks. Activity recognition in real-time provides useful information to enhance the robot's control assistance for daily tasks. This work implemen...

A novel fast method for identifying the origin of Maojian using NIR spectroscopy with deep learning algorithms.

Scientific reports
Maojian is one of China's traditional famous teas. There are many Maojian-producing areas in China. Because of different producing areas and production processes, different Maojian have different market prices. Many merchants will mix Maojian in diff...

Deep learning approach to overcome signal fluctuations in SERS for efficient On-Site trace explosives detection.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Surface-enhanced Raman spectroscopy (SERS) is an improved Raman spectroscopy technique to identify the analyte under study uniquely. At the laboratory scale, SERS has realised a huge potential to detect trace analytes with promising applications acro...

Detecting Hydronephrosis Through Ultrasound Images Using State-of-the-Art Deep Learning Models.

Ultrasound in medicine & biology
The goal of this study was to assess the feasibility of three models for detecting hydronephrosis through ultrasound images using state-of-the-art deep learning algorithms. The diagnosis of hydronephrosis is challenging because of varying and non-spe...

Data augmentation for medical imaging: A systematic literature review.

Computers in biology and medicine
Recent advances in Deep Learning have largely benefited from larger and more diverse training sets. However, collecting large datasets for medical imaging is still a challenge due to privacy concerns and labeling costs. Data augmentation makes it pos...

Fully automatic tumor segmentation of breast ultrasound images with deep learning.

Journal of applied clinical medical physics
BACKGROUND: Breast ultrasound (BUS) imaging is one of the most prevalent approaches for the detection of breast cancers. Tumor segmentation of BUS images can facilitate doctors in localizing tumors and is a necessary step for computer-aided diagnosis...