Review of the state of the art of deep learning for plant diseases: A broad analysis and discussion

RI Hasan, SM Yusuf, L Alzubaidi - Plants, 2020 - mdpi.com
Deep learning (DL) represents the golden era in the machine learning (ML) domain, and it
has gradually become the leading approach in many fields. It is currently playing a vital role …

A systematic review on recent advancements in deep and machine learning based detection and classification of acute lymphoblastic leukemia

PK Das, VA Diya, S Meher, R Panda, A Abraham - IEEE access, 2022 - ieeexplore.ieee.org
Automatic Leukemia or blood cancer detection is a challenging job and is very much
required in healthcare centers. It has a significant role in early diagnosis and treatment …

High accuracy hybrid CNN classifiers for breast cancer detection using mammogram and ultrasound datasets

A Sahu, PK Das, S Meher - Biomedical Signal Processing and Control, 2023 - Elsevier
Breast cancer is a significant cause of cancer fatality among women all over the world.
Hence the detection of this disease at the initial stage works as a boon to the patient so that …

An efficient deep convolutional neural network based detection and classification of acute lymphoblastic leukemia

PK Das, S Meher - Expert Systems with Applications, 2021 - Elsevier
Automated and accurate diagnosis of Acute Lymphoblastic Leukemia (ALL), blood cancer, is
a challenging task. Nowadays, Convolutional Neural Networks (CNNs) have become a …

Deep learning models for classification of red blood cells in microscopy images to aid in sickle cell anemia diagnosis

L Alzubaidi, MA Fadhel, O Al-Shamma, J Zhang… - Electronics, 2020 - mdpi.com
Sickle cell anemia, which is also called sickle cell disease (SCD), is a hematological
disorder that causes occlusion in blood vessels, leading to hurtful episodes and even death …

An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images

A Sahu, PK Das, S Meher - Biomedical Signal Processing and Control, 2024 - Elsevier
Breast cancer is the second major reason of death among women around the world. Early
and accurate breast cancer detection is important for proper treatment planning to save a …

A lightweight deep learning system for automatic detection of blood cancer

PK Das, B Nayak, S Meher - Measurement, 2022 - Elsevier
Microscopic analysis of blood-cells is an essential and vital task for the early diagnosis of life-
threatening hematological disorders like blood cancer (leukemia). We have presented an …

An efficient blood-cell segmentation for the detection of hematological disorders

PK Das, S Meher, R Panda… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The automatic segmentation of blood cells for detecting hematological disorders is a crucial
job. It has a vital role in diagnosis, treatment planning, and output evaluation. The existing …

An efficient detection and classification of acute leukemia using transfer learning and orthogonal softmax layer-based model

PK Das, B Sahoo, S Meher - IEEE/ACM Transactions on …, 2022 - ieeexplore.ieee.org
For the early diagnosis of hematological disorders like blood cancer, microscopic analysis of
blood cells is very important. Traditional deep CNNs lead to overfitting when it receives …

[HTML][HTML] Artificial intelligence in sickle disease

AA Elsabagh, M Elhadary, B Elsayed, AM Elshoeibi… - Blood Reviews, 2023 - Elsevier
Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and
clinical practice in numerous medical fields. Its implications have been rising and are being …