Frank C. Bennis
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View article: A repeated time-to-event model for personalized treatment of patients with hemophilia A based on individual bleeding risk
A repeated time-to-event model for personalized treatment of patients with hemophilia A based on individual bleeding risk Open
The proposed method may present an exciting new treatment paradigm for patients with hemophilia A.
View article: Associations of Clinical Characteristics With Sudden Cardiac Arrest in People With Type 2 Diabetes With and Without Cardiovascular Disease: A Longitudinal Case-Control Study Using Routine Primary Care Data
Associations of Clinical Characteristics With Sudden Cardiac Arrest in People With Type 2 Diabetes With and Without Cardiovascular Disease: A Longitudinal Case-Control Study Using Routine Primary Care Data Open
OBJECTIVE To assess longitudinal associations with sudden cardiac arrest (SCA) of clinical characteristics recorded in primary care in people with type 2 diabetes (T2D), both with and without cardiovascular disease (CVD). RESEARCH DESIGN A…
View article: <b>The associations of clinical characteristics with sudden cardiac arrest in people with type 2 diabetes with and without cardiovascular disease: a longitudinal case-control study using routine primary care data</b>
<b>The associations of clinical characteristics with sudden cardiac arrest in people with type 2 diabetes with and without cardiovascular disease: a longitudinal case-control study using routine primary care data</b> Open
Objective To assess longitudinal associations with sudden cardiac arrest (SCA) of clinical characteristics recorded in primary care in people with type 2 diabetes (T2D), both with and without cardiovascular disease (CVD).Research Design an…
View article: <b>The associations of clinical characteristics with sudden cardiac arrest in people with type 2 diabetes with and without cardiovascular disease: a longitudinal case-control study using routine primary care data</b>
<b>The associations of clinical characteristics with sudden cardiac arrest in people with type 2 diabetes with and without cardiovascular disease: a longitudinal case-control study using routine primary care data</b> Open
Objective To assess longitudinal associations with sudden cardiac arrest (SCA) of clinical characteristics recorded in primary care in people with type 2 diabetes (T2D), both with and without cardiovascular disease (CVD).Research Design an…
View article: Mixed effect estimation in deep compartment models: Variational methods outperform first-order approximations
Mixed effect estimation in deep compartment models: Variational methods outperform first-order approximations Open
View article: The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review
The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review Open
Background Electronic health records (EHRs) contain patients’ health information over time, including possible early indicators of disease. However, the increasing amount of data hinders clinicians from using them. There is accumulating ev…
View article: On inductive biases for the robust and interpretable prediction of drug concentrations using deep compartment models
On inductive biases for the robust and interpretable prediction of drug concentrations using deep compartment models Open
Conventional pharmacokinetic (PK) models contain several useful inductive biases guiding model convergence to more realistic predictions of drug concentrations. Implementing similar biases in standard neural networks can be challenging, bu…
View article: A Generative and Causal Pharmacokinetic Model for Factor <scp>VIII</scp> in Hemophilia A: A Machine Learning Framework for Continuous Model Refinement
A Generative and Causal Pharmacokinetic Model for Factor <span>VIII</span> in Hemophilia A: A Machine Learning Framework for Continuous Model Refinement Open
In rare diseases, such as hemophilia A, the development of accurate population pharmacokinetic (PK) models is often hindered by the limited availability of data. Most PK models are specific to a single recombinant factor VIII (rFVIII) conc…
View article: The added value of temporal data and the best way to handle it: A use-case for atrial fibrillation using general practitioner data
The added value of temporal data and the best way to handle it: A use-case for atrial fibrillation using general practitioner data Open
View article: Using routine primary care data to assess Sudden Cardiac Arrest risk in people with type 2 diabetes: a proof-of-concept case-control study
Using routine primary care data to assess Sudden Cardiac Arrest risk in people with type 2 diabetes: a proof-of-concept case-control study Open
Background Approximately 50% of out-of-hospital Sudden Cardiac Arrest (SCA) occurs in people with unrecognized SCA-risk and no preceding cardiologic care records. General practitioner (GP) records include these people, specifically people …
View article: Embracing cohort heterogeneity in clinical machine learning development: a step toward generalizable models
Embracing cohort heterogeneity in clinical machine learning development: a step toward generalizable models Open
View article: Early identification of persistent somatic symptoms in primary care: data-driven and theory-driven predictive modelling based on electronic medical records of Dutch general practices
Early identification of persistent somatic symptoms in primary care: data-driven and theory-driven predictive modelling based on electronic medical records of Dutch general practices Open
Objective The present study aimed to early identify patients with persistent somatic symptoms (PSS) in primary care by exploring routine care data-based approaches. Design/setting A cohort study based on routine primary care data from 76 g…
View article: The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review (Preprint)
The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review (Preprint) Open
BACKGROUND Electronic health records (EHRs) contain patients’ health information over time, including possible early indicators of disease. However, the increasing amount of data hinders clinicians from using them. There is accumulating e…
View article: Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis
Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis Open
Background Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into acc…
View article: Adoption of Machine Learning in Pharmacometrics: An Overview of Recent Implementations and Their Considerations
Adoption of Machine Learning in Pharmacometrics: An Overview of Recent Implementations and Their Considerations Open
Pharmacometrics is a multidisciplinary field utilizing mathematical models of physiology, pharmacology, and disease to describe and quantify the interactions between medication and patient. As these models become more and more advanced, th…
View article: Pulmonary pathophysiology development of COVID-19 assessed by serial Electrical Impedance Tomography in the MaastrICCht cohort
Pulmonary pathophysiology development of COVID-19 assessed by serial Electrical Impedance Tomography in the MaastrICCht cohort Open
View article: Detection of primary Sjögren’s syndrome in primary care: developing a classification model with the use of routine healthcare data and machine learning
Detection of primary Sjögren’s syndrome in primary care: developing a classification model with the use of routine healthcare data and machine learning Open
View article: Prediction of heart failure 1 year before diagnosis in general practitioner patients using machine learning algorithms: a retrospective case–control study
Prediction of heart failure 1 year before diagnosis in general practitioner patients using machine learning algorithms: a retrospective case–control study Open
Objectives Heart failure (HF) is a commonly occurring health problem with high mortality and morbidity. If potential cases could be detected earlier, it may be possible to intervene earlier, which may slow progression in some patients. Pre…
View article: Diagnostic stewardship for blood cultures in the emergency department: A multicenter validation and prospective evaluation of a machine learning prediction tool
Diagnostic stewardship for blood cultures in the emergency department: A multicenter validation and prospective evaluation of a machine learning prediction tool Open
View article: Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis
Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis Open
Background: Identification of distinct clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment facilitating more personalized treatmen…
View article: Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort (MaastrICCht)
Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort (MaastrICCht) Open
Introduction The course of the disease in SARS-CoV-2 infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patients, we designed the prospective observational M…
View article: Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort;<i>MaastrICCht</i>
Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort;<i>MaastrICCht</i> Open
Background The course of the disease in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patie…
View article: Improving Prediction of Favourable Outcome After 6 Months in Patients with Severe Traumatic Brain Injury Using Physiological Cerebral Parameters in a Multivariable Logistic Regression Model
Improving Prediction of Favourable Outcome After 6 Months in Patients with Severe Traumatic Brain Injury Using Physiological Cerebral Parameters in a Multivariable Logistic Regression Model Open
View article: Artifacts in pulse transit time measurements using standard patient monitoring equipment
Artifacts in pulse transit time measurements using standard patient monitoring equipment Open
Post-processing of the PPG signal in the Masimo module of the Philips patient monitor introduces a sawtooth in PPG and derived PTT. This sawtooth, together with a large module-dependent absolute difference in PTT, renders the thus-derived …
View article: Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis
Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis Open
The support vector machine-based extended model with T-wave morphology markers resulted in a major rise in sensitivity and specificity at the maximal Youden's index. From this, it can be concluded that T-wave morphology assessment has an a…
View article: Letter by Bennis et al Regarding Article, “Cerebral Near-Infrared Spectroscopy: A Potential Approach for Thrombectomy Monitoring”
Letter by Bennis et al Regarding Article, “Cerebral Near-Infrared Spectroscopy: A Potential Approach for Thrombectomy Monitoring” Open
View article: Support Vector Machine Based Monitoring of Cardio-Cerebrovascular Reserve during Simulated Hemorrhage
Support Vector Machine Based Monitoring of Cardio-Cerebrovascular Reserve during Simulated Hemorrhage Open
Introduction: In the initial phase of hypovolemic shock, mean blood pressure (BP) is maintained by sympathetically mediated vasoconstriction rendering BP monitoring insensitive to detect blood loss early. Late detection can result i…
View article: The development and validation of an easy to use automatic QT-interval algorithm
The development and validation of an easy to use automatic QT-interval algorithm Open
Our automated algorithm provides reliable beat-to-beat QT-interval assessment, robust to heart axis and T-wave morphology.