Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
[HTML][HTML] An overview of deep learning in medical imaging
Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …
growth in recent years. The scientific community has focused its attention on DL due to its …
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …
large amount of data to achieve exceptional performance. Unfortunately, many applications …
Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques
This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
Predicting EGFR mutation status in non–small cell lung cancer using artificial intelligence: a systematic review and meta-analysis
Rationale and Objectives Recent advancements in artificial intelligence (AI) render a
substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction …
substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction …
SSP: self-supervised pertaining technique for classification of shoulder implants in x-ray medical images: a broad experimental study
Multiple pathologic conditions can lead to a diseased and symptomatic glenohumeral joint
for which total shoulder arthroplasty (TSA) replacement may be indicated. The long-term …
for which total shoulder arthroplasty (TSA) replacement may be indicated. The long-term …
Trustworthy deep learning framework for the detection of abnormalities in X-ray shoulder images
Musculoskeletal conditions affect an estimated 1.7 billion people worldwide, causing intense
pain and disability. These conditions lead to 30 million emergency room visits yearly, and …
pain and disability. These conditions lead to 30 million emergency room visits yearly, and …
Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …
routines provide unquestionable benefits in connecting human medical expertise with …
A deep learning-based system for survival benefit prediction of tyrosine kinase inhibitors and immune checkpoint inhibitors in stage IV non-small cell lung cancer …
K Deng, L Wang, Y Liu, X Li, Q Hou, M Cao… - …, 2022 - thelancet.com
Background For clinical decision making, it is crucial to identify patients with stage IV non-
small cell lung cancer (NSCLC) who may benefit from tyrosine kinase inhibitors (TKIs) and …
small cell lung cancer (NSCLC) who may benefit from tyrosine kinase inhibitors (TKIs) and …
Deep learning applications for lung cancer diagnosis: a systematic review
Lung cancer has been one of the most prevalent disease in recent years. According to the
research of this field, more than 200,000 cases are identified each year in the US …
research of this field, more than 200,000 cases are identified each year in the US …