Addressing ethical issues in healthcare artificial intelligence using a lifecycle-informed process.

Objectives: Artificial intelligence (AI) proceeds through an iterative and evaluative process of development, use, and refinement which may be characterized as a lifecycle. Within this context, stakeholders can vary in their interests and perceptions of the ethical issues associated with this rapidly evolving technology in ways that can fail to identify and avert adverse outcomes. Identifying issues throughout the AI lifecycle in a systematic manner can facilitate better-informed ethical deliberation.

Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach.

Background: Artificial intelligence (AI) and machine learning (ML) technology design and development continues to be rapid, despite major limitations in its current form as a practice and discipline to address all sociohumanitarian issues and complexities. From these limitations emerges an imperative to strengthen AI and ML literacy in underserved communities and build a more diverse AI and ML design and development workforce engaged in health research.

Objective: AI and ML has the potential to account for and assess a variety of factors that contribute to health and disease and to improve prevention, diagnosis, and therapy.

Crowdsourcing Skin Demarcations of Chronic Graft-Versus-Host Disease in Patient Photographs: Training Versus Performance Study.

Background: Chronic graft-versus-host disease (cGVHD) is a significant cause of long-term morbidity and mortality in patients after allogeneic hematopoietic cell transplantation. Skin is the most commonly affected organ, and visual assessment of cGVHD can have low reliability. Crowdsourcing data from nonexpert participants has been used for numerous medical applications, including image labeling and segmentation tasks.

Co-Encapsulation of Drugs for Topical Application-A Review.

Achieving the best possible outcome for the therapy is the main goal of a medicine. Therefore, nanocarriers and co-delivery strategies were invented to meet this need, as they can benefit many diseases. This approach was applied specifically for cancer treatment, with some success.

Pluronic® triblock copolymer-based nanoformulations for cancer therapy: A 10-year overview.

This paper provides a review of the literature on the use of Pluronic® triblock copolymers for drug encapsulation over the last 10 years. A special focus is given to the progress of drug delivery systems (e.g.

Feasibility and Short-Term Effects of a Multi-Component Emergency Department Blood Pressure Intervention: A Pilot Randomized Trial.

Background Emergency department (ED) visits can be opportunities to address uncontrolled hypertension. We sought to compare short-term blood pressure measures between the Vanderbilt Emergency Room Bundle (VERB) intervention and usual care plus education. Methods and Results We conducted a randomized trial of 206 adult patients with hypertension and elevated systolic blood pressure (SBP) presenting to 2 urban emergency departments in Tennessee, USA.

User preferences for and engagement with text messages to support antihypertensive medication adherence: Findings from a pilot study evaluating an emergency department-based behavioral intervention.

Objective: We examined users' preferences for and engagement with text messages delivered as part of an emergency department (ED)-based intervention to improve antihypertensive medication adherence.

Methods: We recruited ED patients with elevated blood pressure for a pilot randomized trial evaluating a medication adherence intervention with text messages. Intervention participants chose text content and frequency, received texts for 45 days, and completed a feedback survey.

antioxidant and wound healing properties of baru nut extract ( Vog.) in pulmonary epithelial cells for therapeutic application in chronic pulmonary obstructive disease (COPD).

Baru nuts ( Vog.) are a native species from Brazil, rich in phenols and other antioxidants, with high socioeconomic value and possible pharmaceutical applications. Here we investigated baru nut ethanolic extract (BNEE) antioxidant and wound healing activities in human NCI-H441 and A549 lung epithelial cell lines for a possible use in conditions related to oxidative stress and wound healing impairments, such as chronic obstructive pulmonary disease (COPD).

Extracting Medical Information from Paper COVID-19 Assessment Forms.

Objective: This study examines the validity of optical mark recognition, a novel user interface, and crowdsourced data validation to rapidly digitize and extract data from paper COVID-19 assessment forms at a large medical center.

Methods: An optical mark recognition/optical character recognition (OMR/OCR) system was developed to identify fields that were selected on 2,814 paper assessment forms, each with 141 fields which were used to assess potential COVID-19 infections. A novel user interface (UI) displayed mirrored forms showing the scanned assessment forms with OMR results superimposed on the left and an editable web form on the right to improve ease of data validation.

Visualization of aggregate perioperative data improves anesthesia case planning: A randomized, cross-over trial.

Study Objective: A challenge in reducing unwanted care variation is effectively managing the wide variety of performed surgical procedures. While an organization may perform thousands of types of cases, privacy and logistical constraints prevent review of previous cases to learn about prior practices. To bridge this gap, we developed a system for extracting key data from anesthesia records.

Emergency Clinical Procedure Detection With Deep Learning.

Information about a patient's state is critical for hospitals to provide timely care and treatment. Prior work on improving the information flow from emergency medical services (EMS) to hospitals demonstrated the potential of using automated algorithms to detect clinical procedures. However, prior work has not made effective use of video sources that might be available during patient care.

Understanding the Information Needs and Context of Trauma Handoffs to Design Automated Sensing Clinical Documentation Technologies: Qualitative Mixed-Method Study of Military and Civilian Cases.

Background: Current methods of communication between the point of injury and receiving medical facilities rely on verbal communication, supported by brief notes and the memory of the field medic. This communication can be made more complete and reliable with technologies that automatically document the actions of field medics. However, designing state-of-the-art technology for military field personnel and civilian first responders is challenging due to the barriers researchers face in accessing the environment and understanding situated actions and cognitive models employed in the field.

Feasibility Assessment of a Pre-Hospital Automated Sensing Clinical Documentation System.

Clinical documentation in the pre-hospital setting is challenged by limited resources and fast-paced, high-acuity. Military and civilian medics are responsible for performing procedures and treatments to stabilize the patient, while transporting the injured to a trauma facility. Upon arrival, medics typically give a verbal report from memory or informal source of documentation such as a glove or piece of tape.

Automatic Clinical Procedure Detection for Emergency Services.

Understanding a patient's state is critical to providing optimal care. However, information loss occurs during patient hand-offs (e.g.

CYP2C19 Phenotype and Risk of Proton Pump Inhibitor-Associated Infections.

Objectives: Proton pump inhibitors (PPIs) are often used in pediatrics to treat common gastrointestinal disorders, and there are growing concerns for infectious adverse events. Because CYP2C19 inactivates PPIs, genetic variants that increase CYP2C19 function may decrease PPI exposure and infections. We tested the hypothesis that CYP2C19 metabolizer phenotypes are associated with infection event rates in children exposed to PPIs.

In Vivo Restoration of Myocardial Conduction With Carbon Nanotube Fibers.

Background: Impaired myocardial conduction is the underlying mechanism for re-entrant arrhythmias. Carbon nanotube fibers (CNTfs) combine the mechanical properties of suture materials with the conductive properties of metals and may form a restorative solution to impaired myocardial conduction.

Methods: Acute open chest electrophysiology studies were performed in sheep (n=3).

Copy-and-Paste in Medical Student Notes: Extent, Temporal Trends, and Relationship to Scholastic Performance.

Background: Medical students may observe and subsequently perpetuate redundancy in clinical documentation, but the degree of redundancy in student notes and whether there is an association with scholastic performance are unknown.

Objectives: This study sought to quantify redundancy, defined generally as the proportion of similar text between two strings, in medical student notes and evaluate the relationship between note redundancy and objective indicators of student performance.

Methods: Notes generated by medical students rotating through their medicine clerkship during a single academic year at our institution were analyzed.

Prevalence of antimicrobial resistance genes in Bacteroides spp. and Prevotella spp. Dutch clinical isolates.

Objectives: The prevalence of resistance genes in two important anaerobic genera, Bacteroides and Prevotella, was assessed by applying PCR specifically directed to genes of interest.

Methods: A total of 101 Bacteroides spp. and 99 Prevotella spp.

Crowdsourcing to delineate skin affected by chronic graft-vs-host disease.

Background: Estimating the extent of affected skin is an important unmet clinical need both for research and practical management in many diseases. In particular, cutaneous burden of chronic graft-vs-host disease (cGVHD) is a primary outcome in many trials. Despite advances in artificial intelligence and 3D photography, progress toward reliable automated techniques is hindered by limited expert time to delineate cGVHD patient images.

Advancing In-Hospital Clinical Deterioration Prediction Models.

Background: Early warning systems lack robust evidence that they improve patients' outcomes, possibly because of their limitation of predicting binary rather than time-to-event outcomes.

Objectives: To compare the prediction accuracy of 2 statistical modeling strategies (logistic regression and Cox proportional hazards regression) and 2 machine learning strategies (random forest and random survival forest) for in-hospital cardiopulmonary arrest.

Methods: Retrospective cohort study with prediction model development from deidentified electronic health records at an urban academic medical center.

A Crowdsourcing Framework for Medical Data Sets.

Crowdsourcing services like Amazon Mechanical Turk allow researchers to ask questions to crowds of workers and quickly receive high quality labeled responses. However, crowds drawn from the general public are not suitable for labeling sensitive and complex data sets, such as medical records, due to various concerns. Major challenges in building and deploying a crowdsourcing system for medical data include, but are not limited to: managing access rights to sensitive data and ensuring data privacy controls are enforced; identifying workers with the necessary expertise to analyze complex information; and efficiently retrieving relevant information in massive data sets.

Differential Aspartate Usage Identifies a Subset of Cancer Cells Particularly Dependent on OGDH.

Although aberrant metabolism in tumors has been well described, the identification of cancer subsets with particular metabolic vulnerabilities has remained challenging. Here, we conducted an siRNA screen focusing on enzymes involved in the tricarboxylic acid (TCA) cycle and uncovered a striking range of cancer cell dependencies on OGDH, the E1 subunit of the alpha-ketoglutarate dehydrogenase complex. Using an integrative metabolomics approach, we identified differential aspartate utilization, via the malate-aspartate shuttle, as a predictor of whether OGDH is required for proliferation in 3D culture assays and for the growth of xenograft tumors.

Differences in gastric carcinoma microenvironment stratify according to EBV infection intensity: implications for possible immune adjuvant therapy.

Epstein-Barr virus (EBV) is associated with roughly 10% of gastric carcinomas worldwide (EBVaGC). Although previous investigations provide a strong link between EBV and gastric carcinomas, these studies were performed using selected EBV gene probes. Using a cohort of gastric carcinoma RNA-seq data sets from The Cancer Genome Atlas (TCGA), we performed a quantitative and global assessment of EBV gene expression in gastric carcinomas and assessed EBV associated cellular pathway alterations.