Publications by authors named "P S M J Upeksha Samarakoon"
Introduction: Sarcomas are comprised of diverse bone and connective tissue tumors with few effective therapeutic options for locally advanced unresectable and/or metastatic disease. Recent advances in immunotherapy, in particular immune checkpoint inhibition (ICI), have shown promising outcomes in several cancer indications. Unfortunately, ICI therapy has provided only modest clinical responses and seems moderately effective in a subset of the diverse subtypes.
View Article and Find Full Text PDFPrevalence, clinical, and demographic characteristics of concomitant dengue fever and leptospirosis among acute dengue fever patients in The Western Province of Sri Lanka.
WHO South East Asia J Public Health
March 2023
Dengue and leptospirosis are hyperendemic diseases in Sri Lanka. We aimed to determine the prevalence and clinical manifestations of concomitant infections of leptospirosis and acute dengue infection (ADI) in clinically suspected dengue patients. A descriptive cross-sectional study was carried out in five hospitals in the Western Province, from December 2018 to April 2019.
View Article and Find Full Text PDFAccurate and full-length typing of the HLA region is important in many clinical and research settings. With the advent of next generation sequencing (NGS), several HLA typing algorithms have been developed, including many that are applicable to whole exome sequencing (WES). However, most of these solutions operate by providing the closest-matched HLA allele among the known alleles in IPD-IMGT/HLA Database.
View Article and Find Full Text PDFArticle Synopsis
- * A recent white paper, resulting from a strategic meeting of 11 ELIXIR Nodes in September 2018, outlines objectives to tackle CNV challenges like detection, interpretation, and data sharing.
- * The paper suggests ways to align these tasks with ELIXIR's broader strategy and aims to integrate the new ELIXIR Community into the global conversation on genomic research.
Background And Objective: Automatic segmentation of skin lesions is considered a crucial step in Computer-aided Diagnosis (CAD) systems for melanoma detection. Despite its significance, skin lesion segmentation remains an unsolved challenge due to their variability in color, texture, and shapes and indistinguishable boundaries.
Methods: Through this study, we present a new and automatic semantic segmentation network for robust skin lesion segmentation named Dermoscopic Skin Network (DSNet).