[HTML][HTML] A survey on deep learning in COVID-19 diagnosis
According to the World Health Organization statistics, as of 25 October 2022, there have
been 625,248,843 confirmed cases of COVID-19, including 65,622,281 deaths worldwide …
been 625,248,843 confirmed cases of COVID-19, including 65,622,281 deaths worldwide …
[HTML][HTML] Classification framework for medical diagnosis of brain tumor with an effective hybrid transfer learning model
Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the
world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require …
world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require …
Dual adaption based evolutionary algorithm for optimized the smart healthcare communication service of the Internet of Things in smart city
SP Singh, W Viriyasitavat, S Juneja, H Alshahrani… - Physical …, 2022 - Elsevier
Abstract The Internet of Things (IoT) is a revolutionary technique of sharing data for smart
devices that generates huge amounts of data from smart healthcare systems. Therefore …
devices that generates huge amounts of data from smart healthcare systems. Therefore …
Brain tumor detection using VGG19 model on adadelta and SGD optimizer
In both grown-ups and juvenile, brain tumors are the tenth most predominant cause of death
rate. There are many different sorts of tumors, and each one has extremely slim odds of …
rate. There are many different sorts of tumors, and each one has extremely slim odds of …
[HTML][HTML] Ensemble deep learning for brain tumor detection
With the quick evolution of medical technology, the era of big data in medicine is quickly
approaching. The analysis and mining of these data significantly influence the prediction …
approaching. The analysis and mining of these data significantly influence the prediction …
An integration of autonomic computing with multicore systems for performance optimization in Industrial Internet of Things
The goal of this work is to investigate how the self‐awareness characteristic of autonomic
computing, paired with existing performance optimization rules, may be used in applications …
computing, paired with existing performance optimization rules, may be used in applications …
An embedded LSTM based scheme for depression detection and analysis
Depression also known as depressive disorder is a serious and common medical condition
that has an adverse impact on how you feel, think, and behave. But it can also be treated …
that has an adverse impact on how you feel, think, and behave. But it can also be treated …
[PDF][PDF] Classification Framework for Medical Diagnosis of Brain Tumor with an Effective Hybrid Transfer Learning Model. Diagnostics 2022, 12, 2541
Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the
world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require …
world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require …
Analysis of Pulmonary Fibrosis Progression Using Machine Learning Approaches
Pulmonary fibrosis is a progressive lung illness, it usually gets worse over time as the
disease progresses. Scarring develops in the lungs as a result of this condition over time. As …
disease progresses. Scarring develops in the lungs as a result of this condition over time. As …
A Comparative Analysis of Different Models of Deep Learning for Prediction of Renal Cell Carcinoma
V Patel, R Aryan, V Kejriwal… - … Conference on Smart …, 2022 - ieeexplore.ieee.org
RCC (renal cell carcinoma) are one of the most common diseases that can be seen in an old
age group today. For this problem, the technologists give the CT SCAN, MRI, and ultrasound …
age group today. For this problem, the technologists give the CT SCAN, MRI, and ultrasound …