Larpant, Nutcha Niamsi, Wisanu Noiphung, Julaluk Chanakiat, Wipada Sakuldamrongpanich, Tasanee Kittichai, Veerayuth Tongloy, Teerawat Chuwongin, Santhad Boonsang, Siridech Laiwattanapaisal, Wanida
...
Published in
Analytica chimica acta
Both the ABO and Rhesus (Rh) blood groups play crucial roles in blood transfusion medicine. Herein, we report a simple and low-cost paper-based analytical device (PAD) for phenotyping red blood cell (RBC) antigens. Using this Rh typing format, 5 Rh antigens on RBCs can be simultaneously detected and macroscopically visualized within 12 min. The pro...
Karayalçin, Sengim (author)
Some of the most prominent types of attacks against modern cryptographic implementations are side-channel attacks. These attacks leverage some unintended, often physical, leakage of the implementation to retrieve secret information. In recent times, a large part of the focus of side-channel research has been on deep learning methods. These methods ...
Musa, Aminu Hamada, Mohamed Hassan, Mohammed
Published in
SHS Web of Conferences
Despite recent advances in deep learning, the rise of edge devices, and the exponential growth of Internet of Things (IoT) connected devices undermine the performance of deep learning models. It is clear that the future of computing is moving to edge devices. Autonomous vehicles and self-driving cars have leveraged the power of computer vision, esp...
Zhou, H. (author)
Applying deep neural networks (DNNs) for system identification (SYSID) has attracted more andmore attention in recent years. The DNNs, which have universal approximation capabilities for any measurable function, have been successfully implemented in SYSID tasks with typical network structures, e.g., feed-forward neural networks and recurrent neural...
Zhang, Lu Jiang, Yicheng Jin, Zhe Jiang, Wenting Zhang, Bin Wang, Changmiao Wu, Lingeng Chen, Luyan Chen, Qiuying Liu, Shuyi
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Published in
Cancer imaging : the official publication of the International Cancer Imaging Society
Transcatheter arterial chemoembolization (TACE) is the mainstay of therapy for intermediate-stage hepatocellular carcinoma (HCC); yet its efficacy varies between patients with the same tumor stage. Accurate prediction of TACE response remains a major concern to avoid overtreatment. Thus, we aimed to develop and validate an artificial intelligence s...
Liu, Suli Yao, Wu
Published in
BMC bioinformatics
Lung cancer is one of the cancers with the highest mortality rate in China. With the rapid development of high-throughput sequencing technology and the research and application of deep learning methods in recent years, deep neural networks based on gene expression have become a hot research direction in lung cancer diagnosis in recent years, which ...
Bauw, Martin Velasco-Forero, Santiago Angulo, Jesus Adnet, Claude Airiau, Olivier
Near out-of-distribution detection (OOD) aims at discriminating semantically similar data points without the supervision required for classification. This paper puts forward an OOD use case for radar targets detection extensible to other kinds of sensors and detection scenarios. We emphasize the relevance of OOD and its specific supervision require...
LE MOENNE, Christian
International audience
Bourgeais, Victoria Zehraoui, Farida Hanczar, Blaise
Motivation: Medical care is becoming more and more specific to patients’ needs due to the increased availability of omics data. The application to these data of sophisticated machine learning models, in particular deep learning, can improve the field of precision medicine. However, their use in clinics is limited as their predictions are not accomp...
Yasaka, Koichiro Akai, Hiroyuki Sugawara, Haruto Tajima, Taku Akahane, Masaaki Yoshioka, Naoki Kabasawa, Hiroyuki Miyo, Rintaro Ohtomo, Kuni Abe, Osamu
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Published in
Japanese journal of radiology
The purpose of this study was to evaluate whether deep learning reconstruction (DLR) improves the image quality of intracranial magnetic resonance angiography (MRA) at 1.5 T. In this retrospective study, MRA images of 40 patients (21 males and 19 females; mean age, 65.8 ± 13.2 years) were reconstructed with and without the DLR technique (DLR image ...
