Quality metrics

Machine learning has the potential to provide tremendous value to life sciences by providing models that aid in the discovery of new molecules and reduce the time for new products to come to market. Chemical reactions play a significant role in these fields, but there is a lack of high-quality open-source chemical reaction data sets for training machine learning models. Herein, we present ORDerly, an open-source Python package for the customizable and reproducible preparation of reaction data stored in accordance with the increasingly popular Open Reaction Database (ORD) schema...

PURPOSE: Comprehensive geriatric assessment (CGA) is the cornerstone of high-quality care for older adults. There is no current gold standard to guide what should be included as the baseline measure for CGAs. We examined what metrics are being captured in CGA baseline assessments completed by community based integrated care teams in Ireland. METHODS: CGA's care pathways in Ireland are usually initiated with a written document that establish patients baseline in various assessment areas...

PURPOSE: To investigate whether parallel imaging-imposed geometric coil constraints can be relaxed when using a deep learning (DL)-based image reconstruction method as opposed to a traditional non-DL method. THEORY AND METHODS: Traditional and DL-based MR image reconstruction approaches operate in fundamentally different ways: Traditional methods solve a system of equations derived from the image data whereas DL methods use data/target pairs to learn a generalizable reconstruction model...

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years...

Relationships between bacterial taxa are traditionally defined using 16S rRNA nucleotide similarity or average nucleotide identity. Improvements in sequencing technology provides additional pairwise information on genome sequences, which may provide valuable information on genomic relationships. Mapping orthologous gene locations between genome pairs, known as synteny, is typically implemented in the discovery of new species and has not been systematically applied to bacterial genomes. Using a dataset of 378 bacterial genomes, we developed and tested a new measure of synteny similarity between a pair of genomes, which was scaled onto 16S rRNA distance using covariance matrices...

Smilacis Glabrae Rhizoma (SGR ) is recognized in traditional Chinese medicine for its distinctive therapeutic properties and abundant supply. Its phytochemical profile is diverse, encompassing flavonoids, steroids, saccharides, phenolic glycosides, volatile constituents, organic acids, phenylpropanoids, stilbenoids, among others. Recent pharmacological investigations reveal that SGR possesses a broad spectrum of pharmacological effects with multifaceted clinical applications. This review collates the current knowledge on SGR's chemical composition, pharmacological activities, and its clinical utility...

BACKGROUND AND OBJECTIVE: Different training programs have been developed to improve trainee outcomes in urology. However, evidence on the optimal training methodology is sparse. Our aim was to provide a comprehensive description of the training programs available for urological robotic surgery and endourology, assess their validity, and highlight the fundamental elements of future training pathways. METHODS: We systematically reviewed the literature using PubMed/Medline, Embase, and Web of Science databases...

Same Day Emergency Care (SDEC) services are at the heart of recovery plans for Emergency Care in the National Health Service. There are no validated metrics for the quality of care in SDEC. The Society for Acute Medicine's Quality Improvement Committee invited to a three-stage modified Delphi process to gather metrics used by clinicians. Proposed metrics were ranked and further explored by 33 participating experts from a broad range of backgrounds including clinicians, data scientists and operational managers...

OBJECTIVES: Low-value care is associated with increased healthcare costs and direct harm to patients. We sought to develop and validate a simple diagnostic intensity index (DII) to quantify hospital-level diagnostic intensity, defined by the prevalence of advanced imaging among patients with selected clinical diagnoses that may not require imaging, and to describe hospital characteristics associated with high diagnostic intensity. METHODS: We utilized State Inpatient Database data for inpatient hospitalizations with one or more pre-defined discharge diagnoses at acute care hospitals...

This dataset represents a collection of pocket-centric structural data related to protein-protein interactions (PPIs) and PPI-related ligand binding sites. The dataset includes high-quality structural information on more than 23,000 pockets, 3,700 proteins on more than 500 organisms, and nearly 3500 ligands that can aid researchers in the fields of bioinformatics, structural biology, and drug discovery. It encompasses a diverse set of PPI complexes with more than 1,700 unique protein families including some with associated ligands, enabling detailed investigations into molecular interactions at the atomic level...

BACKGROUND: Disability-free life expectancy (DFLE) has been used to gain a better understanding of the population's quality of life. OBJECTIVES: The authors aimed to estimate age and sex-specific disability-free life expectancy (DFLE) for urban and rural areas of Bangladesh, as well as to investigate the differences in DFLE between males and females of urban and rural areas. METHODS: Data from the Bangladesh Sample Vital Statistics-2016 and the Bangladesh Household Income and Expenditure Survey (HIES)-2016 were used to calculate the disability-free life expectancy (DFLE) of urban and rural males and females in Bangladesh in 2016...

BACKGROUND: Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths...

It is commonly suggested that patients' subjective well-being (SWB) can be affected by pre-treatment conditions and treatment experiences, and hence SWB can be used to measure and improve healthcare quality. With data collected in a hospital in the UK ( N  = 446), we investigated the determinants of patients' SWB and evaluated its use in healthcare research. Our findings showed strong relationships between pre-treatment conditions and patients' SWB: anxiety and depression negatively predicted SWB across all three domains, mobility positively predicted the life satisfaction and happiness domains, while the ability to self care and pain and discomfort also predicted SWB in some domains...

INTRODUCTION: Due to a variety of barriers, the majority of cancer survivors do not do enough physical activity to meet current recommendations. This study will assess the feasibility of participation in parkrun walk-run events as a novel mode of community rehabilitation exercise. METHODS: This protocol describes a single-arm intervention study with participants acting as their own controls. The study accepts adults diagnosed with any type of cancer, undergoing treatment or in remission...

RATIONALE AND OBJECTIVES: To investigate the effectiveness of machine learning-based clinical, radiomics, and combined models in differentiating idiopathic granulomatous mastitis (IGM) from malignancy, both presenting as non-mass enhancement (NME) lesions on magnetic resonance imaging (MRI), and to compare these models with radiological evaluation. MATERIAL AND METHODS: A total of 178 patients (69 IGM and 109 breast cancer patients) with NME on breast MRI evaluated between March 2018 and April 2022, were included in this two-center study...

Supervised machine learning-based medical image computing applications necessitate expert label curation, while unlabelled image data might be relatively abundant. Active learning methods aim to prioritise a subset of available image data for expert annotation, for label-efficient model training. We develop a controller neural network that measures priority of images in a sequence of batches, as in batch-mode active learning, for multi-class segmentation tasks. The controller is optimised by rewarding positive task-specific performance gain, within a Markov decision process (MDP) environment that also optimises the task predictor...

Medical image fusion can provide doctors with more detailed data and thus improve the accuracy of disease diagnosis. In recent years, deep learning has been widely used in the field of medical image fusion. The traditional method of medical image fusion is to operate by superimposing and other methods of pixels. The introduction of deep learning methods has improved the effectiveness of medical image fusion. However, these methods still have problems such as edge blurring and information redundancy. In this paper, we propose a deep learning network model based on Transformer and an improved DenseNet network module integration that can be applied to medical images and solve the above problems...

During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics...

PURPOSE: Online resources are increasingly being utilised by patients to guide their clinical decision making, as an alternative or supplement to the traditional clinical-patient relationship. YouTube is an online repository of user and community generated videos, which is one of the most popular websites globally. We undertook a study to examine the quality of information presented in YouTube videos related to tonsillectomy. METHODS: We completed a systematic search of YouTube in May 2023 and identified 88 videos for inclusion in our study...

BACKGROUND: Functional impairment is one of the most decisive prognostic factors in patients with complex chronic diseases. A more significant functional impairment indicates that the disease is progressing, which requires implementing diagnostic and therapeutic actions that stop the exacerbation of the disease. OBJECTIVE: This study aimed to predict alterations in the clinical condition of patients with complex chronic diseases by predicting the Barthel Index (BI), to assess their clinical and functional status using an artificial intelligence model and data collected through an internet of things mobility device...