Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning.

Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. In this study, we applied various machine learning techniques to predict bacterial antibiotic resistance using the Pfizer ATLAS Antibiotics dataset. This comprehensive dataset includes patient demographic data, sample collection details, antibiotic susceptibility test results, and resistance phenotypes for 917,049 bacterial isolates.

A tale of two parasites: a glimpse into the RNA methylome of patient-derived Plasmodium falciparum and Plasmodium vivax isolates.

Background: Understanding the molecular mechanisms of the malarial parasites in hosts is crucial for developing effective treatments. Epitranscriptomic research on pathogens has unveiled the significance of RNA methylation in gene regulation and pathogenesis. This is the first report investigating methylation signatures and alternative splicing events using Nanopore Direct RNA Sequencing to single-base resolution in Plasmodium falciparum and Plasmodium vivax clinical isolates with hepatic dysfunction complications.

Pedestrian Flow Identification and Occupancy Prediction for Indoor Areas.

Indoor localization is used to locate objects and people within buildings where outdoor tracking tools and technologies cannot provide precise results. This paper aims to improve analytics research, focusing on data collected through indoor localization methods. Smart devices recurrently broadcast automatic connectivity requests.

Pedestrian Augmented Reality Navigator.

Navigation is often regarded as one of the most-exciting use cases for Augmented Reality (AR). Current AR Head-Mounted Displays (HMDs) are rather bulky and cumbersome to use and, therefore, do not offer a satisfactory user experience for the mass market yet. However, the latest-generation smartphones offer AR capabilities out of the box, with sometimes even pre-installed apps.

Enabling Agile Clinical and Translational Data Warehousing: Platform Development and Evaluation.

Background: Modern data-driven medical research provides new insights into the development and course of diseases and enables novel methods of clinical decision support. Clinical and translational data warehouses, such as Informatics for Integrating Biology and the Bedside (i2b2) and tranSMART, are important infrastructure components that provide users with unified access to the large heterogeneous data sets needed to realize this and support use cases such as cohort selection, hypothesis generation, and ad hoc data analysis.

Objective: Often, different warehousing platforms are needed to support different use cases and different types of data.

Spontaneous perforation of common bile duct in a young female: An intra-operative surprise.

Introduction: Spontaneous CBD perforation is one of the rare causes of acute abdomen in infants and extremely rare in adults. It is rarely suspected and correctly diagnosed preoperatively.

Presentation Of Case: A 17year old female presented to Emergency Department with sudden onset of pain and distention of abdomen, associated with vomiting and non-passage of flatus and stool for 3days and features of generalized peritonitis.

Gastric GIST or gastric schwannoma-A diagnostic dilemma in a young female.

Introduction: Gastrointestinal stromal tumor (GIST) is the commonest mesenchymal tumor of GI tract and 60-70% of it seen in the stomach, whereas Gastric schwannoma is a benign, slow growing and one of the rare neoplasms of stomach. Age distribution, clinical, radiological features and gross appearance of both tumors are similar.

Presentation Of Case: We report a rare case of gastric schwannoma in a 20-year-old girl, who underwent subtotal gastrectomy with the suspicion of a GIST preoperatively but later confirmed to be gastric schwannoma postoperatively after immunohistochemical study.