Interpreters

Assessing the past habitability of Mars and searching for evidence of ancient life at Jezero crater via the Perseverance rover are the key objectives of NASA's Mars 2020 mission. Onboard the rover, PIXL (Planetary Instrument for X-ray Lithochemistry) is one of the best suited instruments to search for microbial biosignatures due to its ability to characterize chemical composition of fine scale textures in geological targets using a nondestructive technique. PIXL is also the first micro-X-ray fluorescence (XRF) spectrometer onboard a Mars rover...

Background Scuba diving was previously excluded because of hypoglycemic risks for type 1 diabetic patients (T1DM). Specific eligibility criteria and a safety protocol have been defined, while continuous glucose monitoring (CGM) systems have enhanced diabetes management. This study aims to assess the feasibility and accuracy of CGM Dexcom G7 (DG7) and Free Style Libre 3 (FSL3) in a setting of repetitive scuba diving in T1DM, exploring the possibility of non-adjunctive use. Material and methods The study was conducted during an event of Diabete Sommerso® association in November 2023...

The electronic structure of [OsF6 ]2- and PtF6 complexes was studied by means of CASSCF/NEVPT2 multiconfigurational calculations, including spin-orbital coupling, which is very relevant in the case of these metals. From these calculations, it is possible to establish that in the octahedral symmetry ( O h ), the ground state is non-magnetic ( J eff = 0) because of the strong ligand field, and the interaction with paramagnetic excited states is almost negligible, resulting in a non-magnetic behavior, which is in agreement with the experimental evidence...

Conventional supervised learning usually operates under the premise that data are collected from the same underlying population. However, challenges may arise when integrating new data from different populations, resulting in a phenomenon known as dataset shift. This paper focuses on prior probability shift, where the distribution of the outcome varies across datasets but the conditional distribution of features given the outcome remains the same. To tackle the challenges posed by such shift, we propose an estimation algorithm that can efficiently combine information from multiple sources...

Random forests have emerged as a promising tool in comparative metagenomics because they can predict environmental characteristics based on microbial composition in datasets where β-diversity metrics fall short of revealing meaningful relationships between samples. Nevertheless, despite this efficacy, they lack biological insight in tandem with their predictions, potentially hindering scientific advancement. To overcome this limitation, we leverage a geometric characterization of random forests to introduce a data-driven phylogenetic β-diversity metric, the adaptive Haar-like distance...

Machine learning (ML) models are widely employed for crash severity modelling, yet their interpretability remains underexplored. Interpretation is crucial for comprehending ML results and aiding informed decision-making. This study aims to implement an interpretable ML to visualize the impacts of factors on crash severity using 5 years of freeways data from Iran. Methods including classification and regression trees (CART), K-nearest neighbours (KNNs), random forest (RF), artificial neural network (ANN) and support vector machines (SVM) were applied, with RF demonstrating superior accuracy, recall, F1-score and ROC...

BACKGROUND: Belarus and Ukraine were the countries most affected by the consequences of the Chornobyl nuclear power plant in 1986. A study of perinatal mortality in Belarus found a highly statistically significant increase in the 1990s in the most contaminated oblast Gomel but no increase during this period in the rest of Belarus. As a possible mechanism to interpret this increase as a late Chornobyl effect, it has been suggested that strontium-90 contained in Chornobyl fallout, incorporated during menarche, impairs the immune system of pregnant women which in turn increases perinatal mortality...

Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death from sepsis. The aim of this study was to develop an interpretable machine learning model for early prediction of 28-day mortality in patients with SALI. Data from the Medical Information Mart for Intensive Care (MIMIC-IV, v2.2, MIMIC-III, v1.4) were used in this study. The study cohort from MIMIC-IV was randomized to the training set (0.7) and the internal validation set (0.3), with MIMIC-III (2001 to 2008) as external validation...

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is associated with high mortality rates. Despite antibiotic therapy, persistent bacteremia is challenging to treat. Combination therapy with ceftaroline has emerged as a potential treatment option; however, the optimal duration and clinical implications after bacteremia clearance are unknown. METHODS: This retrospective cohort study examined patients with high-grade or persistent MRSA bacteremia who were treated with ceftaroline combination therapy at the University of New Mexico Hospital between January 2014 and June 2021...

The Grief Facilitation Inventory (GFI) assesses caregiver grief facilitation behaviors among bereaved youth. Initial analyses supported the GFI's reliability and validity. The purpose of this study was to evaluate measurement invariance of the GFI across gender, race/ethnicity, and age. Participants were 558 clinic-referred youth aged 7-18 (58.8% female; 43.6% Latino(a), 24.9% White, 14.9% Black, 16.6% Multiracial). Multigroup confirmatory factor analyses provided evidence of measurement invariance for ongoing connection, caregiver grief expression, and existential continuity and support-but not grief inhibition/avoidance-across subgroups...

PURPOSE: Cardiorespiratory fitness (CRF) is a critical marker of overall health and a key predictor of morbidity and mortality, but the existing prediction equations for CRF are primarily derived from general populations and may not be suitable for patients with obesity. METHODS: Predicted CRF from different non-exercise prediction equations was compared with measured CRF of patients with obesity who underwent maximal cardiopulmonary exercise testing (CPET). Multiple linear regression was used to develop a population-specific non-exercise CRF prediction model for treadmill exercise including age, sex, weight, height and physical activity level as determinants...

BACKGROUND: Intraoperative hypotension can lead to postoperative organ dysfunction. Previous studies primarily used invasive arterial pressure as the key biosignal for the detection of hypotension. However, these studies had limitations in incorporating different biosignal modalities and utilizing the periodic nature of biosignals. To address these limitations, we utilized frequency-domain information, which provides key insights that time-domain analysis cannot provide, as revealed by recent advances in deep learning...

Impact dynamics are crucial for estimating the growth patterns of NFT projects by tracking the diffusion and decay of their relative appeal among stakeholders. Machine learning methods for impact dynamics analysis are incomprehensible and rigid in terms of their interpretability and transparency, whilst stakeholders require interactive tools for informed decision-making. Nevertheless, developing such a tool is challenging due to the substantial, heterogeneous NFT transaction data and the requirements for flexible, customized interactions...

Within the ethical debate on Machine Learning-driven decision support systems (ML_CDSS), notions such as "human in the loop" or "meaningful human control" are often cited as being necessary for ethical legitimacy. In addition, ethical principles usually serve as the major point of reference in ethical guidance documents, stating that conflicts between principles need to be weighed and balanced against each other. Starting from a neo-Kantian viewpoint inspired by Onora O'Neill, this article makes a concrete suggestion of how to interpret the role of the "human in the loop" and to overcome the perspective of rivaling ethical principles in the evaluation of AI in health care...

We introduce here a general model of Functional Neurological Disorders based on the following hypothesis: a Functional Neurological Disorder could correspond to a consciously initiated voluntary top-down process causing involuntary lasting consequences that are consciously experienced and subjectively interpreted by the patient as involuntary. We develop this central hypothesis according to Global Neuronal Workspace theory of consciousness, that is particularly suited to describe interactions between conscious and non-conscious cognitive processes...

OBJECTIVE: To evaluate the feasibility of lung ultrasonography (LUS) performed by novice users' general practitioners (GPs) in diagnosing lower respiratory tract infections (LRTIs) in primary health care settings. DESIGN: A prospective interventional multicenter study (December 2019-March 2020). SETTINGS AND SUBJECTS: Patients aged >3 months, suspected of having LRTI consulting in three different general practices (GPs) (rural, semirural and urban) in France...

This viewpoint paper considers the authors' perspectives on the potential role of smartphones, wearables, and other technologies in the diagnosis of cancer. We believe that these technologies could be valuable additions in the pursuit of early cancer diagnosis, as they offer solutions to the timely detection of signals or symptoms and monitoring of subtle changes in behavior that may otherwise be missed. In addition to signal detection, technologies could assist symptom interpretation and guide and facilitate access to health care...

OBJECTIVE: This study evaluates regularization variants in logistic regression (L1, L2, ElasticNet, Adaptive L1, Adaptive ElasticNet, Broken adaptive ridge [BAR], and Iterative hard thresholding [IHT]) for discrimination and calibration performance, focusing on both internal and external validation. MATERIALS AND METHODS: We use data from 5 US claims and electronic health record databases and develop models for various outcomes in a major depressive disorder patient population...

We give examples of three features in the design of randomized controlled clinical trials which can increase power and thus decrease sample size and costs. We consider an example multilevel trial with several levels of clustering. For a fixed number of independent sampling units, we show that power can vary widely with the choice of the level of randomization. We demonstrate that power and interpretability can improve by testing a multivariate outcome rather than an unweighted composite outcome. Finally, we show that using a pooled analytic approach, which analyzes data for all subgroups in a single model, improves power for testing the intervention effect compared to a stratified analysis, which analyzes data for each subgroup in a separate model...

PURPOSE: Age-matched average 3D models facilitate both surgical planning and intraoperative guidance of cranial birth defects such as craniosynostosis. We aimed to develop an algorithm that accepts any number of CT scans as input and generates highly accurate, average models with minimal user input that are ready for 3D printing and clinical use. METHODS: Using a compiled database of 'normal' pediatric computed tomography (CT) scans, we report Normscan, an open-source platform built in Python that allows users to generate normative models of CT scans through user-defined landmarks...