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At least 73 records · Page 4

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.

60 APPLIED LIFE SCIENCES↗

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗

Centromere/kinetochore protein genes for cancer diagnosis, prognosis and treatment selection

The invention described in the application relates to a panel of gene expression markers for patient with a tumor. The invention thus provides methods and compositions, e.g., kits, for evaluating gene expression levels of the markers and methods of using such gene expression levels to evaluate the likelihood of disease progression or response to chemotherapy or radiation therapy. Such information can be used in determining prognosis and treatment options for cancer patients.

59 BASIC BIOLOGICAL SCIENCES↗

Neocytolysis Contributes to the Anemia of Renal Disease

Neocytolysis is a recently described physiologic process effecting selective hemolysis of young red blood cells in circumstances of plethora. Erythropoietin depression appears to initiate the process, providing rationale to investigate its contributions to the anemia of renal disease. When erythropoietin therapy was withheld, four of five stable hemodialysis patients demonstrated Cr-51 red cell survival patterns indicative of neocytolysis; red cell survival was short in the first 9 days, then normalized. Two of these patients received oral (13)C-glycine and (15)N-glycine and showed pathologic enrichment of stool porphyrins by the most recently ingested isotope when EPO therapy was held. This confirms selective hemolysis of newly-released red cells. (One patient had chronic hemolysis by isotope studies of blood and stool.) Thus, neocytolysis can contribute to the anemia of renal disease and explains some unresolved issues about such anemia. One implication is the prediction that intravenous bolus erythropoietin therapy is metabolically and economically inefficient compared to lower doses given more frequently subcutaneously.

Rice, Lawrence↗

Multimodality Instrument for Tissue Characterization

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip is discussed. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network, program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration.

Mah, Robert W.↗

Multimodality instrument for tissue characterization

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration. The use of this system will make surgical procedures safer, more accurate, and more efficient. Other applications of this system include the detection, prognosis and treatment of breast cancer, prostate cancer, spinal diseases, and use in general exploratory surgery.

Mah, Robert W.↗

Neocytolysis contributes to the anemia of renal disease

Neocytolysis is a recently described physiological process affecting the selective hemolysis of young red blood cells in circumstances of plethora. Erythropoietin (EPO) depression appears to initiate the process, providing the rationale to investigate its contributions to the anemia of renal disease. When EPO therapy was withheld, four of five stable hemodialysis patients showed chromium 51 (51Cr)-red cell survival patterns indicative of neocytolysis; red cell survival was short in the first 9 days, then normalized. Two of these four patients received oral 13C-glycine and 15N-glycine, and there was a suggestion of pathological isotope enrichment of stool porphyrins when EPO therapy was held, again supporting selective hemolysis of newly released red cells that take up the isotope (one patient had chronic hemolysis indicated by isotope studies of blood and stool). Thus, neocytolysis can contribute to the anemia of renal disease and explain some unresolved issues about such anemia. One implication is the prediction that intravenous bolus EPO therapy is metabolically and economically inefficient compared with lower doses administered more frequently subcutaneously.

Non-NASA Center↗

Selectively lockable knee brace

A knee brace for aiding in rehabilitation of damaged leg muscles includes upper and lower housings, normally pivotable, one relative to the other about the knee joint axis of a patient. The upper housing is attachable to the thigh of the patient above the knee joint, while the lower housing is secured to a stirrup which extends downwardly along the patient's leg and is attached to the patient's shoe. An actuation rod is carried within the lower housing and is coupled to a cable. The upper and lower housings carry cooperative clutch/brake elements which normally are disengaged to permit relative movement between the upper and lower housings. When the cable is extended, the clutch/brake elements engage and lock the housings together. A heel strike mechanism fastened to the stirrup and the heel of the shoe is connected to the cable to selectively extend the cable and lock the brace in substantially any position when the patient places weight on the heel.

Myers, Neill↗

Selectively Lockable Knee Brace

A knee brace for aiding in rehabilitation of damaged leg muscles includes upper and lower housings normally pivotable one relative to the other about the knee joint axis of a patient. The upper housing is attachable to the thigh of the patient above the knee joint while the lower housing is secured to a stirrup which extends downwardly along the patient's leg and is attached to the patient's shoe. An actuation rod is carried within the lower housing and is coupled to a cable. The upper and lower housings carry cooperative clutch/brake elements which normally are disengaged to permit relative movement between the upper and lower housings. When the cable is extended the clutch/brake elements engage and lock the housings together. A heel strike mechanism fastened to the stirrup and the heel of the shoe is connected to the cable to selectively extend the cable and lock the brace in substantially any position when the patient places weight on the heel.

Myers, W. Neill↗

Disentangling Alzheimer’s disease neurodegeneration from typical brain ageing using machine learning

Abstract Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer’s disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer’s Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T1-weighted MRI scans of 4054 participants (48–95 years) with Alzheimer’s disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer’s disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer’s disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer’s disease continuum group (n = 718; consisting of amyloid-positive Alzheimer’s disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer’s disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer’s disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56–0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer’s disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer’s disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer’s disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer’s disease.

Hwang, Gyujoon↗

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1). To address the critical need for novel therapeutics in MPNST, we aimed to establish an ex vivo 3D platform that accurately captured the genomic diversity of MPNST and could be utilized in a medium-throughput manner for drug screening studies to be validated in vivo using patient-derived xenografts (PDX). Genomic analysis was performed on all PDX-tumor pairs. Selected PDX were harvested for assembly into 3D microtissues. Based on prior work in our labs, we evaluated drugs (trabectedin, olaparib, and mirdametinib) ex vivo and in vivo. For 3D microtissue studies, cell viability was the endpoint as assessed by Zeiss Axio Observer. For PDX drug studies, tumor volume was measured twice weekly. Bulk RNA sequencing was performed to identify pathways enriched in cells. We developed 13 NF1-associated MPNST-PDX and identified mutations or structural abnormalities in NF1 (100%), SUZ12 (85%), EED (15%), TP53 (15%), CDKN2A (85%), and chromosome 8 gain (77%). We successfully assembled PDX into 3D microtissues, categorized as robust (>90% viability at 48 h), good (>50%), or unusable (<50%). We evaluated drug response to “robust” or “good” microtissues, namely MN-2, JH-2-002, JH-2-079-c, and WU-225. Drug response ex vivo predicted drug response in vivo, and enhanced drug effects were observed in select models. These data support the successful establishment of a novel 3D platform for drug discovery and MPNST biology exploration in a system representative of the human condition.

60 APPLIED LIFE SCIENCES↗

Endogenous circulating sympatholytic factor in orthostatic intolerance

Sympathotonic orthostatic hypotension (SOH) is an idiopathic syndrome characterized by tachycardia, hypotension, elevated plasma norepinephrine, and symptoms of orthostatic intolerance provoked by assumption of an upright posture. We studied a woman with severe progressive SOH with blood pressure unresponsive to the pressor effects of alpha(1)-adrenergic receptor (AR) agonists. We tested the hypothesis that a circulating factor in this patient interferes with vascular adrenergic neurotransmission. Preincubation of porcine pulmonary artery vessel rings with patient plasma produced a dose-dependent inhibition of vasoconstriction to phenylephrine in vitro, abolished vasoconstriction to direct electrical stimulation, and had no effect on nonadrenergic vasoconstrictive stimuli (endothelin-1), PGF-2alpha (or KCl). Preincubation of vessels with control plasma was devoid of these effects. SOH plasma inhibited the binding of an alpha(1)-selective antagonist radioligand ([(125)I]HEAT) to membrane fractions derived from porcine pulmonary artery vessel rings, rat liver, and cell lines selectively overexpressing human ARs of the alpha(1B) subtype but not other AR subtypes (alpha(1A) and alpha(1D)). We conclude that a factor in SOH plasma can selectively and irreversibly inhibit adrenergic ligand binding to alpha(1B) ARs. We propose that this factor contributes to a novel pathogenesis for SOH in this patient. This patient's syndrome represents a new disease entity, and her plasma may provide a unique tool for probing the selective functions of alpha(1)-ARs.

Case Reports↗

Effect of oral plaque control on postoperative pneumonia following lung cancer surgery

Abstract Background There have been few studies on the relationship between oral status and postoperative pneumonia (POP) in patients with lung cancer, and whether improving their oral condition assists with a lower incidence of POP before lung cancer surgery remains controversial. This retrospective study was conducted by a stomatologist to assess the effect of controlling oral pathogenic bacteria of patients with lung cancer to prevent POP. Methods A total of 235 patients with lung cancer who underwent lobectomy by open thoracotomy between July 2015 and December 2018 were selected and given the choice of being in the experimental or control group. A total of 122 participants in the experimental group received professional oral plaque control, and 113 participants in the control group did not receive plaque control. All clinical data of participants in both groups were retrospectively studied to determine the incidence of POP at the thirtieth day of discharge from hospital. Results Eight in the experimental group and six in the control group were excluded from the study. It was found that four of 114 patients suffered from POP in the experimental group (incidence = 3.51%). A total of 17 of 107 patients in the control group had pulmonary infection (incidence = 15.89%). Odds ratio was 0.19. The incidence of POP in the experimental group was significantly lower than that of the control group ( P < 0.05). Conclusions Professional oral plaque control is associated with a lower incidence of POP following lung cancer surgery and is therefore a favorable factor for preventing POP, and should be carried out before the surgical treatment of lung cancer. Key points Professional oral plaque control was associated with a lower incidence of POP following lung cancer surgery, and it is recommended this should be carried out before the surgical treatment of lung cancer.

Jia, Chunling↗

Diagnostic, Prognostic, and Therapeutic Use of Radiopharmaceuticals in the Context of SARS-CoV-2

The coronavirus disease 2019 (COVID-19) outbreak has devastated the healthcare systems and economies of over 200 countries in just a few months. The etiological agent of COVID-19, SARS-CoV-2, is a highly contagious virus that can be transmitted by asymptomatic and symptomatic carriers alike. While in vitro testing techniques have allowed for population-wide screening, prognostic tools are required to assess the disease severity and therapeutic response, contributing to improve the patient clinical outcomes. Moreover, no specific antiviral against COVID-19 exists at the time of publication, severely limiting treatment against the infection. Hence, there is an urgent clinical need for innovative therapeutic strategies that may contribute to manage the COVID-19 outbreak and prevent future pandemics. In this work, we critically examine recent diagnostic, prognostic, and therapeutic advancements for COVID-19 in the field of radiopharmaceuticals. First, we summarize the gold standard techniques used to diagnose COVID-19, including in vitro assays and imaging techniques, and then discuss how radionuclide-based nuclear imaging provides complementary information for prognosis and treatment management of infected patients. Second, we introduce new emerging types of radiotherapies that employ radioimmunoconjugates, which have shown selective cytotoxic response in oncological studies, and critically analyze how these compounds could be used as therapeutic agents against SARS-CoV-2. Finally, this Perspective further discusses the emerging applications of radionuclides to study the behavior of pulmonary SARS-CoV-2 aerosol particles.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DLK1 is a GATA1s-driven dependency and therapeutic target in Down syndrome–associated myeloid leukemia

Children with Down syndrome have a markedly increased risk of developing myeloid leukemia. Although having an excellent prognosis, 10% to 20% develop relapsed or refractory disease with poor survival, highlighting the need for new targeted approaches. The pathogenesis of myeloid leukemia of Down syndrome (ML-DS) is tightly linked to fetal hematopoiesis and mutations in GATA1, generating the truncated GATA1 short (GATA1s) isoform. We identified Delta-like noncanonical Notch ligand 1 (DLK1) as a direct GATA1s target. DLK1, a paternally imprinted transmembrane protein, is highly expressed in fetal liver CD34 + cells but absent in adult hematopoiesis, making it an attractive immunotherapeutic target. Chromatin profiling revealed GATA1s occupancy at a distal enhancer within the DLK1-DIO3 locus, driving aberrant DLK1 upregulation in ML-DS. Functional studies demonstrated that DLK1 is a leukemia dependency, as its genetic ablation impaired proliferation and engraftment, induced apoptosis, and altered Notch and β-catenin signaling. Therapeutically, a DLK1-directed antibody-drug conjugate–induced selective cytotoxicity, abrogated colony formation, and significantly prolonged survival in refractory ML-DS patient-derived xenograft (PDX) models, achieving durable remissions at higher doses. These findings establish DLK1 as a leukemia-specific vulnerability and provide preclinical proof-of-concept for DLK1-targeted therapies in ML-DS and other leukemias with fetal-like expression programs.

Biological and medical sciences↗

Baseline [ 18 F]GTP1 tau PET imaging is associated with subsequent cognitive decline in Alzheimer’s disease

Background: The role and implementation of tau PET imaging for predicting subsequent cognitive decline in Alzheimer’s disease (AD) remains uncertain. This study was designed to evaluate the relationship between baseline [ 18 F]GTP1 tau PET and subsequent longitudinal change across multiple cognitive measures over 18 months. Methods: Our analyses incorporated data from 67 participants, including cognitively normal controls (n = 10) and β-amyloid (Aβ)-positive individuals ([ 18 F] florbetapir Aβ PET) with prodromal (n = 26), mild (n = 16), or moderate (n = 15) AD. Baseline measurements included cortical volume (MRI), tau burden ([ 18 F]GTP1 tau PET), and cognitive assessments [Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR), 13-item version of the Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13), and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)]. Cognitive assessments were repeated at 6-month intervals over an 18-month period. Associations between baseline [ 18 F]GTP1 tau PET indices and longitudinal cognitive performance were assessed via univariate (Spearman correlations) and multivariate (linear mixed effects models) approaches. The utility of potential prognostic tau PET cut points was assessed with ROC curves. Results: Univariate analyses indicated that greater baseline [ 18 F]GTP1 tau PET signal was associated with faster rates of subsequent decline on the MMSE, CDR, and ADAS-Cog13 across regions of interest (ROIs). In multivariate analyses adjusted for baseline age, cognitive performance, cortical volume, and Aβ PET SUVR, the prognostic performance of [ 18 F]GTP1 SUVR was most robust in the whole cortical gray ROI. When AD participants were dichotomized into low versus high tau subgroups based on baseline [ 18 F]GTP1 PET standardized uptake value ratios (SUVR) in the temporal (cutoff = 1.325) or whole cortical gray (cutoff = 1.245) ROIs, high tau subgroups demonstrated significantly more decline on the MMSE, CDR, and ADAS-Cog13. Conclusions: Our results suggest that [ 18 F]GTP1 tau PET represents a prognostic biomarker in AD and are consistent with data from other tau PET tracers. Tau PET imaging may have utility for identifying AD patients at risk for more rapid cognitive decline and for stratification and/or enrichment of participant selection in AD clinical trials.

60 APPLIED LIFE SCIENCES↗

Time-based priority selection for analog circuits

Unlimited channel capacity multiplexing circuit is hierarchially structured to achieve priority encoding. Circuit could be used for automatic patient monitoring systems and diagnostic test systems in automotive and communications industry.

Fageol, J. D.↗

Characterizing Sub-Cohorts via Data Normalization and Representation Learning

The process of identifying a cohort of interest is a very challenging task. It requires manually inspecting many patient records of complex structure that might include medical coding errors and missing data. This paper presents a computational pipeline for refining the process of cohort selection based on medical concepts recorded in the electronic health records (EHRs). The pipeline extracts EHR data for a given cohort and normalizes this data using standard vocabularies. Then a stacked denoising autoencoder is used to embed the normalized patient vectors in a low dimensional space, where the patients are subsequently clustered into sub-cohorts. The goal is to represent the cohort in a standard format and abstract variants of sub-populations. As a use-case, we applied the pipeline to 1.8 million Veterans diagnosed with major depressive disorder (MDD), and identified four meaningful sub-cohorts using the features learned by the autoencoder. Then, each sub-cohort was explored using a set of keywords for interpretation.

Rush III, Everett↗