Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models from the RSNA 2022 Cervical Spine Fracture AI Challenge.

Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on re-evaluation; such studies do not capture the full extent of missed fractures. To use machine-learning (ML) models to identify cervical spine fractures on CT missed by interpreting radiologists, characterize the nature of these fractures, and assess their clinical significance. This retrospective study included all cervical spine CT examinations performed in adult patients in the emergency department between January 1, 2018 and December 31, 2022.

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and Methods The competition was hosted on Kaggle and took place between July 26 and October 15, 2023. The multicenter competition dataset consisted of 4274 abdominal trauma CT scans, in which solid organs (liver, spleen, and kidneys) were annotated as healthy, low-grade, or high-grade injury.

Ambulance Transports from NCAA Division 1 Football Games.

Introduction: There is significant public health interest towards providing medical care at mass-gathering events. Furthermore, mass gatherings have the potential to have a detrimental impact on the availability of already-limited municipal Emergency Medical Services (EMS) resources. This study presents a cross-sectional descriptive analysis to report broad trends regarding patients who were transported from National Collegiate Athletic Association (NCAA) Division 1 collegiate football games at a major public university in order to better inform emergency preparedness and resource planning for mass gatherings.

Decreased GABA levels during development result in increased connectivity in the larval zebrafish tectum.

γ-aminobutyric acid (GABA) is an abundant neurotransmitter that plays multiple roles in the vertebrate central nervous system (CNS). In the early developing CNS, GABAergic signaling acts to depolarize cells. It mediates several aspects of neural development, including cell proliferation, neuronal migration, neurite growth, and synapse formation, as well as the development of critical periods.

Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center.

Purpose To evaluate the performance of the top models from the RSNA 2022 Cervical Spine Fracture Detection challenge on a clinical test dataset of both noncontrast and contrast-enhanced CT scans acquired at a level I trauma center. Materials and Methods Seven top-performing models in the RSNA 2022 Cervical Spine Fracture Detection challenge were retrospectively evaluated on a clinical test set of 1828 CT scans (from 1829 series: 130 positive for fracture, 1699 negative for fracture; 1308 noncontrast, 521 contrast enhanced) from 1779 patients (mean age, 55.8 years ± 22.

Lysine from Whole Wheat Bread Consumed by Healthy Adult Males Has High Metabolic Availability When Assessed Using the Indicator Amino Acid Oxidation Method.

Background: The protein quality of wheat is limited by its low content of the indispensable amino acid (AA) lysine and the metabolic availability (MA) of lysine in wheat bread for humans is unknown.

Objectives: The study objective was to determine the MA of lysine in whole wheat bread.

Methods: Five healthy young males (≤30 y, body mass index <25) were studied in a repeated-measures design using the indicator amino acid oxidation (IAAO) method, with L-[1-C] phenylalanine as the indicator.

Enhancing Postmarketing Surveillance of Medical Products With Large Language Models.

Importance: The Sentinel System is a key component of the US Food and Drug Administration (FDA) postmarketing safety surveillance commitment and uses clinical health care data to conduct analyses to inform drug labeling and safety communications, FDA advisory committee meetings, and other regulatory decisions. However, observational data are frequently deemed insufficient for reliable evaluation of safety concerns owing to limitations in underlying data or methodology. Advances in large language models (LLMs) provide new opportunities to address some of these limitations.

Total sulfur amino acid requirements are higher during late gestation compared with early gestation in healthy Canadian pregnancies in a repeated-measures trial.

Background: Dietary Reference Intake (DRI) Recommendations for total sulfur amino acids (TSAAs; methionine + cysteine) during pregnancy are based on factorial calculations using data from adult males. To date, no data exist on TSAA requirements obtained directly during pregnancy.

Objectives: The objective of this study was to examine whether TSAA requirements during early (11-20 wk) and late (31-40 wk) gestation in healthy females with singleton pregnancies are different than current recommendations, and different between early and late gestation using the indicator amino acid oxidation (IAAO) technique.

Invited commentary: A future of data-rich pharmacoepidemiology studies- transitioning to large-scale linked EHR+claims data.

Electronic health record (EHR) data are seen as an important source for Pharmacoepidemiology studies. In the US healthcare system, EHR systems often only identify fragments of patients' health information across the care continuum, including primary care, specialist care, hospitalizations, and pharmacy dispensing. This leads to unobservable information in longitudinal evaluations of medication effects causing unmeasured confounding, misclassification, and truncated follow-up times.

Trust but Verify: Lessons Learned for the Application of AI to Case-Based Clinical Decision-Making From Postmarketing Drug Safety Assessment at the US Food and Drug Administration.

Adverse drug reactions are a common cause of morbidity in health care. The US Food and Drug Administration (FDA) evaluates individual case safety reports of adverse events (AEs) after submission to the FDA Adverse Event Reporting System as part of its surveillance activities. Over the past decade, the FDA has explored the application of artificial intelligence (AI) to evaluate these reports to improve the efficiency and scientific rigor of the process.

A simulation-based bias analysis to assess the impact of unmeasured confounding when designing nonrandomized database studies.

Unmeasured confounding is often raised as a source of potential bias during the design of nonrandomized studies, but quantifying such concerns is challenging. We developed a simulation-based approach to assess the potential impact of unmeasured confounding during the study design stage. The approach involved generation of hypothetical individual-level cohorts using realistic parameters, including a binary treatment (prevalence 25%), a time-to-event outcome (incidence 5%), 13 measured covariates, a binary unmeasured confounder (u1; 10%), and a binary measured "proxy" variable (p1) correlated with u1.

Studying the cellular basis of small bowel enteropathy using high-parameter flow cytometry in mouse models of primary antibody deficiency.

Background: Primary immunodeficiencies are heritable defects in immune system function. Antibody deficiency is the most common form of primary immunodeficiency in humans, can be caused by abnormalities in both the development and activation of B cells, and may result from B-cell-intrinsic defects or defective responses by other cells relevant to humoral immunity. Inflammatory gastrointestinal complications are commonly observed in antibody-deficient patients, but the underlying immune mechanisms driving this are largely undefined.

A general framework for developing computable clinical phenotype algorithms.

Objective: To present a general framework providing high-level guidance to developers of computable algorithms for identifying patients with specific clinical conditions (phenotypes) through a variety of approaches, including but not limited to machine learning and natural language processing methods to incorporate rich electronic health record data.

Materials And Methods: Drawing on extensive prior phenotyping experiences and insights derived from 3 algorithm development projects conducted specifically for this purpose, our team with expertise in clinical medicine, statistics, informatics, pharmacoepidemiology, and healthcare data science methods conceptualized stages of development and corresponding sets of principles, strategies, and practical guidelines for improving the algorithm development process.

Results: We propose 5 stages of algorithm development and corresponding principles, strategies, and guidelines: (1) assessing fitness-for-purpose, (2) creating gold standard data, (3) feature engineering, (4) model development, and (5) model evaluation.

Dietary Lysine Requirements of Older Adults Stratified by Age and Sex.

Background: Current recommendation for lysine in older adults, 30 mg/kg/d, is based on young adult data. Evidence suggests that amino acid requirements may differ between young and old adults with both sex and age having an effect in the elderly.

Objectives: This study aimed to define the lysine requirements in healthy older adults using the indicator amino acid oxidation (IAAO) method with L-[1-C] phenylalanine as the indicator and to compare the derived estimates based on age: 60-69 y and >70 y.

Effects of altering diet carbohydrate profile and physical form on zoo-housed giraffe Giraffa camelopardalis reticulata.

Unlike wild giraffe that primarily consume low starch browse, the preference of zoo-housed giraffe for consuming supplemental feeds over forage could increase the risk of digestive disorders such as ruminal acidosis. Our objective was to evaluate the effects of modifying a supplemental feed's non-fibre carbohydrate profile and physical form on nutritional, behavioural, and blood measures of giraffe in a zoological setting. Six non-lactating, adult, female reticulated giraffes were used in a two-pen modified reversal study using two dietary treatments in seven 21-day periods with data collected on days 15-21.

Vibrational anisotropy decay resolves rare earth binding induced conformational change in DTPA.

Elucidating the relationship between metal-ligand interactions and the associated conformational change of the ligand is critical for understanding the separation of lanthanides ion binding. Here we examine DTPA, a multidentate ligand that binds lanthanides, in its free and metal bound conformations using ultrafast polarization dependent vibrational spectroscopy. The polarization dependent pump-probe spectra were analyzed to extract the isotropic and anisotropic response of DTPA's carbonyl groups in the 1550-1650 cm spectral region.

Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges.

The Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organizing these competitions, with a specific emphasis on the creation and curation of high-quality datasets. The collection of diverse and representative medical imaging data involves dealing with issues of patient privacy and data security.

Studying the cellular basis of small bowel enteropathy using high-parameter flow cytometry in mouse models of primary antibody deficiency.

Background: Primary immunodeficiencies are heritable defects in immune system function. Antibody deficiency is the most common form of primary immunodeficiency in humans, can be caused by abnormalities in both the development and activation of B cells, and may result from B-cell-intrinsic defects or defective responses by other cells relevant to humoral immunity. Inflammatory gastrointestinal complications are commonly observed in antibody-deficient patients, but the underlying immune mechanisms driving this are largely undefined.