A review of medical image segmentation algorithms
KKD Ramesh, GK Kumar, K Swapna… - … on Pervasive Health …, 2021 - publications.eai.eu
… the computational speed in the process of medical image … , treatment planning and follow
up studies; However, methods … for evaluating the breast and cyst mass [11]. These algorithms …
up studies; However, methods … for evaluating the breast and cyst mass [11]. These algorithms …
Medical imaging using machine learning and deep learning algorithms: a review
… This paper provides a survey of medical imaging in the machine and deep learning
methods to analyze distinctive diseases. It carries consideration concerning the suite of these …
methods to analyze distinctive diseases. It carries consideration concerning the suite of these …
[HTML][HTML] Early prediction of sepsis from clinical data: the PhysioNet/Computing in Cardiology Challenge 2019
… medical classification problems ( 15 ). In 2019, the Challenge’s 20th year, we asked participants
to develop automated techniques … utility scores on test data from hospital systems A, B, …
to develop automated techniques … utility scores on test data from hospital systems A, B, …
A review of deep learning based methods for medical image multi-organ segmentation
… to be contoured for treatment planning. We grouped the surveyed … The time analysis reported
in this study shows that the … be limited due to large computation complexity. Unlike CNN …
in this study shows that the … be limited due to large computation complexity. Unlike CNN …
Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives
… these techniques intensively in the health sector for the analysis … individual’s health condition
and process the data obtained … As the computational power and sensing capabilities of the …
and process the data obtained … As the computational power and sensing capabilities of the …
Edge computing for smart health: Context-aware approaches, opportunities, and challenges
… -EOG monitoring system as a case study and present an efficient technique that deals with …
In summary, at the MEN, our SAE encoder converts the input data x into the compressed data …
In summary, at the MEN, our SAE encoder converts the input data x into the compressed data …
[HTML][HTML] Development of metaverse for intelligent healthcare
… has greatly advanced medical imaging, testing the limits of … computational limitations and
uncertainties in biological models make this approach impractical for routine treatment planning…
uncertainties in biological models make this approach impractical for routine treatment planning…
Edge computing for Internet of Things: A survey, e-healthcare case study and future direction
… (2012) developed a system which continuously monitors … analyzed by the KAA edge computing
server, the analyzed data is … -making process becomes faster and easier in the e-health …
server, the analyzed data is … -making process becomes faster and easier in the e-health …
[HTML][HTML] Brain tumor analysis empowered with deep learning: A review, taxonomy, and future challenges
… , recognition procedures and treatment plans for cancer patients. … method, as the images
have more mass. The proposed … in the domain of soft computing and medical images. Machine …
have more mass. The proposed … in the domain of soft computing and medical images. Machine …
TCM network pharmacology: a new trend towards combining computational, experimental and clinical approaches
W Xin, W Zi-Yi, JH Zheng, LI Shao - Chinese journal of natural medicines, 2021 - Elsevier
… To verify the mechanism and material basis of a TCM … and after YinXieLing treatment for
proteomic testing and further … by combining computational and experimental methods and to …
proteomic testing and further … by combining computational and experimental methods and to …