Articles in 2024

May et al. propose machine learning algorithms that leverage QRS polarity direction and shifts to differentiate wide QRS complex tachycardias. Strong diagnostic accuracy is demonstrated, particularly when integrating features from both wide QRS tachycardia and baseline electrocardiograms.

Loria, Tabernacki et al. investigate the risk of eating disorder diagnoses among transgender and gender-diverse individuals. Transfeminine individuals on hormone therapy are more likely to be diagnosed with eating disorders, while transmasculine individuals on hormone or surgical therapy are less likely to receive such diagnoses.

Shaaban et al. undertake personalized metabolic modeling of the infant gut microbiome during the first year of life. The gut microbiome of infants delivered through Cesarian section has reduced metabolic capabilities compared with that of vaginally delivered infants at early time points, and infant gut microbiomes are enriched in B-vitamin biosynthesis compared with adult gut microbiomes.

Yuan and Qiu et al. estimate heritability for High Myopia (HM) using whole-exome sequencing data in Han Chinese ancestry and European ancestry. By combining rare risk genotypes with exome-wide association studies of HM, the authors develop an exome-wide genetic risk score for HM prediction.

Sukul et al. analyze exhaled metabolites to find endogenous volatile markers indicative of postmenopausal osteoporosis. The non-invasive breath analysis serves as more rapid and reliable classification of osteoporosis risk when compared to conventional serum bone markers and includes markers of gut-bone axis.

Koch et al. model scenarios of emergence of a single pan-resistant Escherichia coli strain in the United States. Findings suggest dire mortality outcomes and highlight the importance of measures to prevent the emergence of antimicrobial resistance.

Zhang et al. investigate how the large body of publicly available images from the biomedical domain can be used to generate a new medical visual question-answering dataset. Along with the resulting benchmark dataset, the authors propose a novel visual-language model and compare its performance against existing approaches.

Shamai et al. develop and validate a deep learning system for predicting receptor status from H&E images in breast cancer. The system accurately identifies hormone receptor-positive patients and detects false negative diagnoses, supporting its integration into clinical workflows to improve diagnostic accuracy, patient care, and quality assurance.

Ria et al. develop a mathematical framework for estimating total risk of an imaging procedure that accounts for both radiation and clinical risks. The authors propose a model that accounts for a variety of factors including disease prevalence, false positive rate, and expected life-expectancy loss.

Harris et al. evaluate Fc-dependent functional antibodies with two widely used COVID vaccines in vaccinated Brazilian adults. Vaccine and natural immunity underlie the differences observed in Fcγ-receptor-binding (types I, IIa, and IIIa/b), IgG, IgM, and IgA production, and complement-fixing antibodies.

Mocking et al. address the need for enhanced detection of measurable residual disease (MRD) in leukemia utilizing flow cytometry and computational methods. Their fully automated assessment of MRD status produces interpretable results for clinical diagnostic experts.

Auvinen et al. examine genome-wide DNA methylation, imprinting, and gene expression in human placentas. Placentas from assisted reproductive technologies experience a variety of altered signaling pathways with variability based on method providing insight into subfertility.

Wang, Kapolowicz, Li et al. investigate the effect of cochlear implantation on tinnitus in postlingually deafened individuals with or without pre-surgical tinnitus. There is a low risk of cochlear implants causing tinnitus but a high chance of them suppressing tinnitus, with a fast tinnitus suppression mechanism relating to device activation and a slow one that relates to brain plasticity.

Posada-Quintero et al. study the dynamics of the electrodermal activity and heart rate while breathing at elevated oxygen partial pressures in a hyperbaric environment. Electrodermal activitycan be used to predict the onset of central nervous system oxygen toxicity symptoms in divers resulting from prolonged exposure to a hyperbaric environment.

Chang et al. convert white light cystoscopy (WLC) images collected with standard-of-care clinical equipment into accurate blue light cystoscopy (BLC)-like images. By introducing key pre-processing steps to circumvent color and brightness variations in clinical datasets, they provide enhanced sensitivity without labor or equipment cost.

Wei et al. investigate the link between accelerated biological aging and the risk of musculoskeletal disorders, highlighting sex-related disparities. Age acceleration significantly increases the risk and onset of nine musculoskeletal disorders, with notable differences between males and females.

Dungu et al. use high throughput multiplexed proteomics on dried blood spot samples from neonates with herpes simplex virus infection. Distinct protein profiles were seen in proteins associated with innate and adaptive immune responses neonates with disseminated HSV disease compared to controls.

Nguyen et al. present IMML, an interpretable multimodal machine learning framework that utilizes prior biological knowledge, integrating multiomic and clinical data. IMML successfully predicts and identifies putative modifiable biomarkers for incident distal sensorimotor polyneuropathy.

Valik et al. incorporate genomic biomarkers from Pseudomonas aeruginosa isolates and clinical data into machine-learning models to predict the severity of bloodstream infection. Bacterial virulence markers identified through whole genome sequencing offer prognostic insights that could inform treatment strategies in sepsis management.

Bloemeke et al. develop a method for measuring Aβ oligomers in plasma to diagnose Alzheimer’s Disease. Correlation analysis between cerebral spinal fluid and plasma oligomer concentrations indicates an impaired clearance of Aβ oligomers that is dependent on ApoE ε4 status.