Publications by authors named "Isha Bhatia"
Article Synopsis
- Lung cancer has a high mortality rate, but early prediction can significantly reduce risks; current prediction methods face challenges like low accuracy and high false-positive rates.
- This research introduces a novel algorithm that combines two deep neural networks (WDSI and SS-CL) to enhance early lung cancer detection using 3D CT scan images from the LUNA16 dataset.
- The proposed lightweight model achieves impressive results with 98.2% accuracy, improved noise reduction, and efficiency metrics (32.8% PSNR and 0.97 SSIM), showing promise for better medical image analysis and patient outcomes.
Lung cancer, also known as lung carcinoma, has a high death rate, but an early diagnosis can substantially reduce this risk. In the current era, prediction models face challenges such as low accuracy, excessive noise, and low contrast. To resolve these problems, an advanced lung carcinoma prediction and risk screening model using transfer learning is proposed.
View Article and Find Full Text PDFTo study the clinico-etiological profile of children with thrombocytopeniaMethods: This prospective hospital-based study included all children (<18 years) with thrombocytopenia at the time of hospitalization and/or thrombocytopenia during the course of their hospital stay. A detailed history was recorded and appropriate laboratory investigations were carried out Results: The study group comprised 246 children (mean age, 9.29 years; median age, 10 years) with male to female ratio of 1.
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