The Complete Inpatient Record Using Comprehensive Electronic Data (CIRCE) project: A team-based approach to clinically validated, research-ready electronic health record data.

Introduction: The rapid adoption of electronic health record (EHR) systems has resulted in extensive archives of data relevant to clinical research, hospital operations, and the development of learning health systems. However, EHR data are not frequently available, cleaned, standardized, validated, and ready for use by stakeholders. We describe an in-progress effort to overcome these challenges with cooperative, systematic data extraction and validation.

Squeezed dual-comb spectroscopy.

Optical frequency combs have enabled unique advantages in broadband, high-resolution spectroscopy and precision interferometry. However, quantum mechanics ultimately limits the metrological precision achievable with laser frequency combs. Quantum squeezing has led to significant measurement improvements with continuous wave lasers, but experiments demonstrating metrological advantage with squeezed combs are less developed.

Resting State Functional Connectivity of the Default Mode Network During Opioid Use and Cessation in Treatment-Seeking Persons.

Resting-state functional connectivity analyses have been used to examine synchrony in neural networks in substance use disorders (SUDs), with the default mode network (DMN) one of the most studied. Prior research has generally found less DMN synchrony during use and greater synchrony during cessation, although little research has utilized this method with opioid use. This study examined resting brain activity in treatment-seeking persons who use opioids at two points-when using opioids and when opioid-free-to determine whether the DMN exhibits different levels of connectivity during opioid use and cessation and whether differences in connectivity predict subsequent relapse.

Synergizing quantum techniques with machine learning for advancing drug discovery challenge.

The Quantum Computing for Drug Discovery Challenge, held at the 42nd International Conference on Computer-Aided Design (ICCAD) in 2023, was a multi-month, research-intensive competition. Over 70 teams from more than 65 organizations from 12 different countries registered, focusing on the use of quantum computing for drug discovery. The challenge centered on designing algorithms to accurately estimate the ground state energy of molecules, specifically OH+, using quantum computing techniques.