Research and Reviews: Journal of Oncology and Hematology
Volume 14, Issue 2 (2025)
Table of contents
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Evaluating the Role of Platelet Indices, with a Focus on Immature Platelet Fraction (IPF), in Differentiating Hyper-Destructive and Hypo-Productive Thrombocytopenia: A Study from Ludhiana, Punjab, India
Abstract: Background: Thrombocytopenia, characterized by a reduction in platelet count, is commonly observed in clinical settings. Its etiology can be broadly classified into hyper-destructive thrombocytopenia, where platelets are destroyed at an accelerated rate, and hypo-productive thrombocytopenia, where platelet production is impaired. Differentiating between these two causes is essential for effective management. The Immature Platelet Fraction (IPF) has emerged as a promising non-invasive diagnostic tool to distinguish these causes. Objectives: The primary …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Ovarian Cancer: Understanding Risk Factors, Diagnosis, and Advances in Treatment
Abstract: Ovarian cancer is a leading cause of cancer-related mortality among women worldwide, often diagnosed at advanced stages due to its subtle early symptoms. Ovarian cancer develops due to a combination of factors, including genetics, environmental influences, and hormonal changes. This article explores the pathophysiology of ovarian cancer, highlighting the genetic mutations, such as BRCA1 and BRCA2, that contribute to its development. It also discusses current diagnostic methods, including imaging techniques …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Cancer as one of the major diseases rank in the World is still very challenging to diagnose and treat hence need for the technological advancements. Chemotherapy, radiation, as well as surgery therapies have several drawbacks including non-selective action, damage to healthy tissues, and multi-drug resistance. Smart nano-theranostics, an advanced integration of nanotechnology with diagnostic and therapeutic modalities, offers a next-generation approach for precision oncology. Thus, the development of multifunctional nanoparticles …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article