Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
A survey on deep learning and machine learning techniques over histopathology image based Osteosarcoma Detection
KV Deepak, R Bharanidharan - Multimedia Tools and Applications, 2024 - Springer
Osteosarcoma is a common type of cancer that occurs in the cells and spreads to the bones.
Osteosarcoma can develop due to genetic mutations, but most cases are not inherited. It …
Osteosarcoma can develop due to genetic mutations, but most cases are not inherited. It …
Optimization of deep neural networks for multiclassification of dental X-rays using transfer learning
GD Deepak, S Krishna Bhat - Computer Methods in Biomechanics …, 2024 - Taylor & Francis
In this work, the segmented dental X-ray images obtained by dentists have been classified
into ideal/minimally compromised edentulous area (no clinical treatment needed …
into ideal/minimally compromised edentulous area (no clinical treatment needed …
Drivers Drowsiness Detection using Image Processing and I-Ear Techniques
Fatigue and micro-sleep at the wheel are often the cause of serious accidents.
Consequently, the initial signs of micro-sleep can be detected before a critical situation …
Consequently, the initial signs of micro-sleep can be detected before a critical situation …
Enhancing the Zebra Optimization Algorithm with Chaotic Sinusoidal Map for Versatile Optimization
D Anand, OI Khalaf… - Iraqi Journal For …, 2024 - ijcsm.researchcommons.org
In this study, the Chaotic Sinusoidal Map (CSM)-enhanced Zebra Optimization Algorithm
(CZOA) is introduced. CZOA combines CSM's integration strengths with ZOA's optimization …
(CZOA) is introduced. CZOA combines CSM's integration strengths with ZOA's optimization …
Epileptic seizure classification using fuzzy lattices and Neural Reinforcement Learning
ABSTRACT This work uses Fuzzy Lattices and Neural Reinforcement Learning techniques
for seizure classification. EEG database of Bonn University and CHB-MIT has been used for …
for seizure classification. EEG database of Bonn University and CHB-MIT has been used for …
Hybrid generative model for grading the severity of diabetic retinopathy images
R Bhuvaneswari, M Diviya… - Computer Methods in …, 2024 - Taylor & Francis
One of the common eye conditions affecting patients with diabetes is diabetic retinopathy
(DR). It is characterised by the progressive impairment to the blood vessels with the increase …
(DR). It is characterised by the progressive impairment to the blood vessels with the increase …
Original Research Article Identification of meningioma tumor using recurrent neural networks
D Anand, OI Khalaf, GM Abdulsahib… - Journal of Autonomous …, 2024 - jai.front-sci.com
By the calculations of national center for biotechnology information from COVID 19
pandemic, number of meningioma tumor patients are increasing in world. Identifying the …
pandemic, number of meningioma tumor patients are increasing in world. Identifying the …
[HTML][HTML] Detection of bone cancer based on a four-phase framework generative deep belief neural network in deep learning
R Aarthy, V Muthupriya, GN Balaji - Alexandria Engineering Journal, 2024 - Elsevier
The medical image processing plays an important role in analyzing and detecting tumors
and detecting cancer cells in their early stages. Microscopic images were used as a deep …
and detecting cancer cells in their early stages. Microscopic images were used as a deep …
Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning
Early and accurate diagnosis of osteosarcomas (OS) is of great clinical significance, and
machine learning (ML) based methods are increasingly adopted. However, current ML …
machine learning (ML) based methods are increasingly adopted. However, current ML …