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Research and Reviews: Journal of Oncology and Hematology

rrjooh | E-ISSN: 2319-3387 | Peer-Reviewed | Hybrid Open Access

About the Journal

Research and Reviews: Journal of Oncology and Hematology [2319-3387(e)] is a peer-reviewed open access journal launched in 2012 focused on the publication of current research work carried out at all the major research centers in the fields of Oncology and Haematology

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Research & Reviews: Journal of Oncology and Hematology (RRJOOH): 2319-3387(e) 

Journal Information

Title:
Research & Reviews: Journal of Oncology and Hematology
Abbreviation:
RRJOOH
Issues Per Year:
3 Issues (Jan-April,May-August,Sept-Dec)
P-ISSN:
2319-3387
Publisher:
116314
DOI:
10.37591/RRJoOH
Starting Year:
2012
Subject:
Language:
English
Publication Format:
Hybrid Open Access
Copyright Policy:
CC BY-NC-ND
Type:
Peer-reviewed Journal (Refereed Journal)
Address:

Editorial Board

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rrjooh maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Dillip Kumar Parida, Professor and Head

AIIMS Bhubaneswar, Orissa, India,

Email :

Latest Articles

Transforming Cancer Care Through AI-Driven Machine Learning: Real-Time Patient Monitoring and Personalized Intervention Strategies

Modern healthcare systems are being improved by artificial intelligence (AI) and machine learning (ML), particularly in the treatment of cancer.

Artificial intelligence, machine learning, cancer patient monitoring, real-time health monitoring, personalized intervention, smart healthcare, digital health

Anticancer, Bioactive, & Therapeutic Applications of Cannabinoids

Cannabinoids, a complex class of lipophilic compounds found in Cannabis sativa L., are attracting significant clinical interest for their multifaceted therapeutic potential, particularly within oncology.

Angiogenesis, anticancer therapy, apoptosis, bioactive compounds, cannabis, oncology

A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes

One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection.

Convolutional neural networks, graph convolutional networks, radiomics, CT, MRI, machine learning, deep learning, hepatocellular carcinoma, and liver cancer

The Quiet Intruder: An Insidious Presentation of Primary Plasma Cell Leukemia and a Literature Review on Current Treatment Strategies

Primary plasma cell leukemia (pPCL) is a rare and aggressive plasma cell dyscrasia, defined by ≥5% circulating plasma cells, with poor prognosis and rapid progression.

Plasma cell leukemia, multiple myeloma, hypercalcemia, monoclonal gammopathy, proteasome inhibitors

Early Lung Cancer Prediction using deep Learning

Lung cancer is a global killer because it’s often found late.

Early lung cancer detection, Deep learning, Convolutional neural networks, ResNet50, DenseNet201, EfficientNet-B0, Medical imaging.

Extracellular Vesicle-Based Liquid Biopsies: Decoding the Tumor Microenvironment for Precision Oncology

The tumor microenvironment (TME) plays a pivotal role in cancer initiation, progression, and therapeutic response.

Cancer biomarkers, Exosomes, Extracellular vesicles, Immune modulation, Liquid biopsy, Metastasis, Microfluidics, Multiomics, Nano-diagnostics, Precision oncology, Therapy resistance, Tumor/Tumour microenvironment

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