Computer-aided diagnosis of liver cancer with improved SegNet and deep stacking ensemble model.

Liver cancer is a leading cause of cancer-related deaths, often diagnosed at advanced stages due to reliance on traditional imaging methods. Existing computer-aided diagnosis systems struggle with noise, anatomical complexity, and ineffective feature integration, leading to inaccuracies in lesion segmentation and classification. By effectively addressing these challenges, the model aims to enhance early detection and assist clinicians in making informed decisions.

Liver Cancer Diagnosis: Enhanced Deep Maxout Model with Improved Feature Set.

This work proposed a liver cancer classification scheme that includes Preprocessing, Feature extraction, and classification stages. The source images are pre-processed using Gaussian filtering. For segmentation, this work proposes a LUV transformation-based adaptive thresholding-based segmentation process.

Evaluation of thermo-adaptability between Tharparkar (Bos indicus) and crossbred (Bos indicus X Bos taurus) calves in a controlled environment.

The global warming driven climate change has increased the susceptibility of livestock around the globe to heat stress (HS), which reduces animal productivity and threatens the sustainability of marginal farmers. The objective of this investigation was to evaluate thermo-adaptability between Tharparkar calves (TC), an indigenous milch breed of India and crossbred calves (CC) during induced heat stress in controlled environment. For this purpose, 12 apparently healthy male calves (six in each group) aged 5-6 months, were selected.

Chronic Lymphocytic Leukemia: Real-World Data From India.

Purpose: Chronic lymphocytic leukemia (CLL) is uncommon in India. There are limited studies on CLL from the Indian subcontinent.

Methods: This was a prospective study (2011-2017) of consecutively diagnosed patients with CLL at a single center.