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Results for “Model interpretability”

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At least 91 records · Page 5Linked to original sources
PubMed1978

Corneal temperatures--a study of normal and laser-injured corneas in the Dutch belted rabbit.

Air Force laser safety standards are developed from laser-exposure data obtained in studies using experimental animals and from biomathematical modeling procedures. Interpretation of research data and predictive modeling calculations are enhanced by knowledge of the temperature values of the tissue absorption sites. Corneal temperature values for the normal, the anesthetized, and the laser-injured Dutch belted rabbit are presented and compared with values obtained in other studies. The corneal temperatures were measured by infrared radiometry.

Anesthesia, Intravenous↗
PubMed1991

Risk models for rebleeding and postoperative mortality in bleeding gastric ulcer.

In order to better define management policies we attempted to construct risk models for rebleeding on initial conservative management and mortality after emergency surgery for failure of medical therapy in 387 patients with bleeding gastric ulcer. Several different models were constructed using logistic regression analysis with validation by the 'leaving-one-out' method. However, despite large patient numbers, modelling in this way is difficult because of inherent wide variation between patients. Suitable models for rebleeding were regarded as rather unsatisfactory, for although overall accuracy was 86%, sensitivity was only 54%. More promising was a model for mortality after emergency surgery which had an accuracy of 93% and a sensitivity of 80%. Such mortality models incorporating age, history of previous malignant disease or dyspepsia, the presence or absence of ascites and total transfusion requirements may well prove to be of value in surgical practice. This paper seeks to examine the process of modelling rebleeding and mortality and of interpreting the models produced.

Aged↗
PubMed2026

GT-Mamba: a Topology-Aware Graph-State space model for robust and interpretable epigenetic age prediction.

MOTIVATION: Current epigenetic clocks face a trade-off between predictive accuracy and biological interpretability, often relying on dataset-specific correction to generalize across cohorts. We propose GT-Mamba, a novel architecture that integrates a Structure-Aware Graph Transformer with the Mamba state space model. This design captures CpG topological correlations and genome-wide long-range dependencies. RESULTS: GT-Mamba demonstrates strong out-of-the-box robustness across heterogeneous independent validation cohorts, achieving a weighted average MAE of 4.43 years. Notably, it effectively generalizes to EPIC 850k arrays despite partial feature missingness, and maintains consistent performance across homologous age distribution shifts (MAE 2.94 years in a young cohort). Ablation studies confirm that graph topology contributes to improved robustness against noise. Mechanistic analysis suggests that the model captures methylation patterns associated with both developmental and functional processes. AVAILABILITY: Source code and pre-trained models are freely available at https://github.com/NENUBioCompute/GT-Mamba and archived on Zenodo (DOI: 10.5281/zenodo.19703155).

Epigenesis, Genetic↗
PubMed1991

Identification of antibody epitopes within the CB-11 peptide of type II collagen. II. Computer modelling studies of peptides and the interpretation of epitope scanning results.

Computer modelling techniques were used to investigate the structure of 8-mers from the CB-11 peptide of bovine type II collagen which were recognised by sera from rats which had previously been injected with bovine type II collage. It was discovered that all the hydrophobic peptides recognised by the rat sera were predicted to have collagenous-like secondary structures. The primary structure of the 8-mers which were recognised was also compared against the sequences in the OWL protein sequence database. The combined results of the computer modelling and sequence analysis suggested that the sequence Gly-Pro-Gly-Phe-Pro is a minimal B cell epitope of the CB-11 fragment of bovine type II collagen.

Amino Acid Sequence↗
PubMed1977

Electrical properties of frog skeletal muscle fibers interpreted with a mesh model of the tubular system.

This paper presents the construction, derivation, and test of a mesh model for the electrical properties of the transverse tubular system (T-system) in skeletal muscle. We model the irregular system of tubules as a random network of miniature transmission lines, using differential equations to describe the potential between the nodes and difference equations to describe the potential at the nodes. The solution to the equations can be accurately represented in several approximate forms with simple physical and graphical interpretations. All the parameters of the solution are specified by impedance and morphometric measurements. The effect of wide circumferential spacing between T-system openings is analyzed and the resulting restricted mesh model is shown to be approximated by a mesh with an access resistance. The continuous limit of the mesh model is shown to have the same form as the disk model of the T-system, but with a different expression for the tortuosity factor. The physical meaning of the tortuosity factor is examined, and a short derivation of the disk model is presented that gives results identical to the continuous limit of the mesh model. Both the mesh and restricted mesh models are compared with experimental data on the impedance of muscle fibers of the frog sartorius. The derived value for the resistivity of the lumen of the tubules is not too different from that of the bathing solution, the difference probably arising from the sensitivity of this value to errors in the morphometric measurements.

Animals↗
PubMed1975

An anatomical, histochemical, and autoradiographic study of the ever-growing molar dentition of Microtus with comments on the role of structure in growth and eruption.

An analysis of the microanatomy of the molar dentition of Microtus utilizing histological, histochemical and autoradiographic techniques reveals a complex architecture with distinctive morphogenic mechanisms which respond to the functional requirements of the organism. These mechanisms include; the maintenance of continued growth and eruption of the molars to compensate for continued hard tissue loss from wear at the occlusal surface of the crown throughout the entire lifespan of the orgainism and a positive feedback repair mechanism to protect the growth systems from the potential destruction this normal occlusal wear could initiate. An awareness and understanding of these phenomena is of significant value for interpreting palentological specimens and formulating a theoretical model for interpreting the evolution of Microtine molar dentitions.

Alveolar Process↗
PubMed1992

Anticoagulation therapy advisor: a decision-support system for heparin therapy during ECMO.

We present a case study describing our development of a mathematical model to control a clinical parameter in a patient--in this case, the degree of anticoagulation during extracorporeal membrane oxygenation (ECMO) support. During ECMO therapy, an anticoagulant agent (heparin) is administered to prevent thrombosis. Under- or over-coagulation can have grave consequences. To improve control of anticoagulation, we developed a pharmacokinetic-pharmacodynamic (PK-PD) model that predicts activated clotting times (ACT) using the NONMEM program. We then integrated this model into a decision-support system, and validated it with an independent data set. The population model had a mean absolute error of prediction for ACT values of 33.5 seconds, with a mean bias in estimation of -14.3 seconds. Individualization of model-parameter estimates using nonlinear regression improved the absolute error prediction to 25.5 seconds, and lowered the mean bias to -3.1 seconds. The PK-PD model is coupled with software for heuristic interpretation of model results to provide a complete environment for the management of anticoagulation.

Blood Coagulation Disorders↗
PubMed2026

Factors influencing the enhancement of the new iron triangle in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise´s Multiplication Appliqué´ a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans↗
PubMed2026

Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

BACKGROUND: Predicting enterocutaneous fistula (ECF)-associated sepsis and mortality poses significant challenges in digital health care due to the disease's complexity and heterogeneous clinical manifestations. Current approaches that rely on single-modal data or traditional scoring systems often fail to capture the intricate immune-inflammatory dynamics and multisystem involvement in patients with ECF. OBJECTIVE: This study aims to develop an artificial intelligence (AI)-driven multimodal fusion model integrating clinical, imaging, and transcriptomic data for early prediction of ECF-associated sepsis and 28-day mortality, addressing the limitations of conventional single-dimensional models. METHODS: This study leveraged publicly available datasets (Medical Information Mart for Intensive Care III [MIMIC-III], electronic Intensive Care Unit [eICU], and The Cancer Genome Atlas) to construct a multimodal framework. Clinical parameters were processed using Extreme Gradient Boosting, abdominal imaging features were extracted via convolutional neural networks, and transcriptomic profiles were analyzed with variational autoencoders. A Transformer-based fusion network was employed for joint prediction and validated through cross-validation and external testing. Key features were identified using Shapley Additive Explanations and Local Interpretable Model-Agnostic Explanations interpretability algorithms, while immune regulatory mechanisms were explored via weighted gene co-expression network analysis. RESULTS: The multimodal model achieved an area under the curve (AUC) of 0.89 for predicting sepsis and 28-day mortality, outperforming unimodal models (clinical-only model, AUC 0.72, and imaging-only model, AUC 0.78). Critical predictors included Sequential Organ Failure Assessment score, lactate levels, intra-abdominal free fluid on imaging, and immunoregulatory genes (programmed death-ligand 1 [PD-L1] and indoleamine 2,3-dioxygenase 1 [IDO1]). Mechanistic analysis revealed distinct immune reprogramming in patients with sepsis, characterized by increased regulatory T cells and M2 macrophages, along with downregulated cluster of differentiation 8+ (CD8+) T cells. CONCLUSIONS: This multimodal AI model offers an innovative digital solution in medical informatics, enabling precise early risk stratification for ECF-associated sepsis. By integrating multisource data and providing interpretable insights into immune-inflammatory pathways, the model enhances health care quality for patients with ECF and paves the way for personalized intervention strategies.

Humans↗
PubMed1990

An empirical model for analysing and interpreting ventricular measures.

Given the abundant and, at times, contradictory studies of ventricular enlargement in neurological and psychiatric disorders, the current study was carried out to provide an empirical basis for analysing and interpreting these measures. A sample of CT scans on 100 control subject was drawn from the files of the University of British Columbia Department of Radiology and 19 measures of ventricular and head diameter or area were made. The interrelationships of these measures were then examined using factor analytic procedures. Three ventricular dimensions were found. To validate these three dimensions, the relationship of each with age was examined and then the age-corrected scores of seven clinical groups were compared on each of these dimensions. The magnitude of the relationship between these dimensions and age was impressive and each dimension contributed unique information regarding these age-related changes. Moreover, the analysis of the clinical groups suggested that differential patterns of ventricular change were present dependent upon the disease. These results are discussed with a view to integrating the findings of previous studies and planning future studies.

Adult↗
PubMed1979

Metabolism of totally ischemic excised dog heart. II. Interpretation of a computer model.

Analysis of the ischemic dog heart preparation described in the preceding paper indicates that it is an analogue in slow motion of the tissue in the center of a cardiac infarct. It is respiring very slowly and not capable of performing mechanical work. Glycolysis starts up with both glucose and glycogen as inputs. Later hexokinase and to some extent phosphofructokinase become limiting owing to inhibitor accumulation or acidosis. Metabolism then results primarily from cAMP-driven glycogenolysis, largely limited by the glycogen debranching enzymes at later times, with accumultion not only of lactate and alpha-glycerophosphate but of glucose as well. Amino acid levels oscillate with time while fatty acids accumulate at late times. The elevation of cAMP at later times may involve disturbances in its metabolism as well as mechanisms such as adenosine accumulation that are more important in cardiac ischemia than in normal heart. The clinical implications of this behavior are discussed.

Amino Acids↗
PubMed1991

Effects of gene mutations in lipoprotein and hepatic lipases as interpreted by a molecular model of the pancreatic triglyceride lipase.

A molecular model of human pancreatic lipase (Winkler, F. K., D'Arcy, A., and Hunziker, W. (1990) Nature 343, 771-774) is used to explain the possible structural effects of the amino acid mutations identified to date in the human lipoprotein and hepatic lipase genes. A sequence homology profile was used to evaluate the alignment of the amino acid sequences of all three lipolytic enzymes (Kirchgessner, T. G., Chuat, J.-C., Heinzmann, C., Etienne, J., Guilhot, S., Svenson, K., Ameis, D., Pilon, C., D'Auriol, L., Andalibi, A., Schotz, M. C., Galibert, F., and Lusis, A. J. (1989) Proc. Natl. Acad. Sci. U. S. A. 86, 9647-9651) with respect to the secondary structure elements identified in the pancreatic lipase. As expected, maximum homology is observed in internal regions namely the hydrophobic strands of the central beta-pleated sheet. This observation strongly supports the hypothesis that all three molecules exhibit a very similar three-dimensional structure, particularly in the N-terminal catalytic domain. There is considerable variation in some of the surface loops connecting the individual strands, whereas others are conserved. It is hypothesized that the most conserved loops located around the active site are responsible for the catalytic function (similar for all three enzymes), whereas those that markedly differ are involved in the regulation at the molecular level, namely the binding of colipase (pancreatic enzyme) and apolipoprotein CII (lipoprotein lipase). The currently available library of hepatic and lipoprotein gene mutations seems to indicate that the majority of mutants disrupt the folding of the polypeptide chain, rather than affect specific constellations in and around the catalytic site or regulatory loops.

Amino Acid Sequence↗
PubMed1990

Uncertainties in pharmacokinetic modeling for perchloroethylene. I. Comparison of model structure, parameters, and predictions for low-dose metabolism rates for models derived by different authors.

In recent years physiologically based pharmacokinetic models have come to play an increasingly important role in risk assessment for carcinogens. The hope is that they can help open the black box between external exposure and carcinogenic effects to experimental observations, and improve both high-dose to low-dose and interspecies projections of risk. However, to date, there have been only relatively preliminary efforts to assess the uncertainties in current modeling results. In this paper we compare the physiologically based pharmacokinetic models (and model predictions of risk-related overall metabolism) that have been produced by seven different sets of authors for perchloroethylene (tetrachloroethylene). The most striking conclusion from the data is that most of the differences in risk-related model predictions are attributable to the choice of the data sets used for calibrating the metabolic parameters. Second, it is clear that the bottom-line differences among the model predictions are appreciable. Overall, the ratios of low-dose human to bioassay rodent metabolism spanned a 30-fold range for the six available human/rat comparisons, and the seven predicted ratios of low-dose human to bioassay mouse metabolism spanned a 13-fold range. (The greater range for the rat/human comparison is attributable to a structural assumption by one author group of competing linear and saturable pathways, and their conclusion that the dangerous saturable pathway constitutes a minor fraction of metabolism in rats.) It is clear that there are a number of opportunities for modelers to make different choices of model structure, interpretive assumptions, and calibrating data in the process of constructing pharmacokinetic models for use in estimating "delivered" or "biologically effective" dose for carcinogenesis risk assessments. We believe that in presenting the results of such modeling studies, it is important for researchers to explore the results of alternative, reasonably likely approaches for interpreting the available data--and either show that any conclusions they make are relatively insensitive to particular interpretive choices, or to acknowledge the differences in conclusions that would result from plausible alternative views of the world.

Animals↗
PubMed1977

[Electronic measuring and calculating devices for arcogrammetric model diagnosis and for the interpretation of teleradiographs].

A newly developed method to mesure different parameters from plaster models of the teeth, from dental radiographs and from cephalometric X-rays by means of a 4-K minicomputer and on-line linear transducers are described. Programs in connection to Arcogrammetrics [Herren] are presented. The electronic devices allow storage of these parameters in order to make drawings of the actual dental arches and of predicted arches, as well as to trace growth and/or progress in orthodontic treatment.

Cephalometry↗
PubMed1989

Variability of safe dose estimates when using complicated models of the carcinogenic process. A case study: methylene chloride.

Advances in understanding carcinogenesis have led to the development of mathematical models that have biologically interpretable parameters. These models utilize more of the available scientific data than the empirical models routinely employed for quantifying carcinogenic risk. They also require consideration of sources of uncertainty in risk estimates that were previously ignored, such as animal-to-animal variability of physiological and pharmacological constants. A numerical technique is proposed for studying the consequences of incorporating the intrapopulation variability of biologically interpretable parameters into the risk assessment process. To demonstrate the technique, the variability of safe dose estimates for exposure to methylene chloride is considered. The results suggest that intrapopulation variability of the model parameters can increase the variability of safe dose estimates an appreciable amount.

Animals↗
PubMed2026

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy.

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Databases, Protein↗
PubMed1991

Analysis of failure time data with ordinal categories of response.

When failure times are observed, additional information concerning the type of failure is often recorded. A method which simultaneously models the failure times and additional information in the form of ordinal categories is discussed. An application to clinical trial data, in which the failure times are times of onset of headache, and the headaches are classified into the ordinal categories mild, moderate and severe, illustrates how this method may be used and how the final model can be interpreted. The continuation ratio model, which is used in this method, is described in detail.

Clinical Trials as Topic↗