Insight into the seroepidemiology and dynamics of circulating serotypes of dengue virus over a 4 year period in western Uttar Pradesh, India.

An important public health problem in India is dengue infection, with every year seeing an increase in cases of dengue fever. Dengue affects all individuals irrespective of their gender and age, although the infection rate is higher among males and younger people. Despite low severity in general, dengue virus can cause severe health conditions in some individuals.

Development of artificial intelligence system for quality control of photo documentation in esophagogastroduodenoscopy.

Background: Esophagogastroduodenoscopy (EGD) is generally a safe procedure, but adverse events often occur. This highlights the necessity of the quality control of EGD. Complete visualization and photo documentation of upper gastrointestinal (UGI) tracts are important measures in quality control of EGD.

Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks.

Convolutional neural networks (CNNs), a popular type of deep neural network, have been actively applied to image recognition, object detection, object localization, semantic segmentation, and object instance segmentation. Accordingly, the applicability of deep learning to the analysis of medical images has increased. This paper presents a novel application of state-of-the-art CNN models, such as DenseNet, to the automatic detection of the tympanic membrane (TM) and middle ear (ME) infection.

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy.

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vision methods applied to endoscopy and promoting the development of new approaches suitable for clinical translation. Endoscopy is a routine imaging technique for the detection, diagnosis and treatment of diseases in hollow-organs; the esophagus, stomach, colon, uterus and the bladder.

A Multi-Organ Nucleus Segmentation Challenge.

Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop generalizable nuclei segmentation techniques in digital pathology. The challenge was an official satellite event of the MICCAI 2018 conference in which 32 teams with more than 80 participants from geographically diverse institutes participated.

CARLo-7-A plausible biomarker for bladder cancer.

Cancer is defined as undifferentiated and unchecked growth of cells damaging the surrounding tissue. Cancers manifest altered gene expression. Gene expression is regulated by a diverse array of non-protein-coding RNA.

Revisiting ligand-induced conformational changes in proteins: essence, advancements, implications and future challenges.

Ligand-induced conformational changes are of immense importance for the biological activity of a protein. An in-depth understanding of salutary and deleterious effects of ligand-induced conformational alterations in single- and multi-chain proteins would lend a hand in human welfare. Unlike single-chain proteins, the function of multichain proteins depends upon the inherent properties of the subunit interfaces.