Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective

This paper presents a Lisp architecture for a portable NLP system, termed LAPNLP, for processing clinical notes. LAPNLP integrates multiple standard, customized and in-house developed NLP tools. Our system facilitates portability across different institutions and data systems by incorporating an enriched Common Data Model (CDM) to standardize necessary data elements. It utilizes UMLS to perform domain adaptation when integrating generic domain NLP tools. It also features stand-off annotations that are specified by positional reference to the original document. We built an interval tree based search engine to efficiently query and retrieve the stand-off annotations by specifying positional requirements. We also developed a utility to convert an inline annotation format to stand-off annotations to enable the reuse of clinical text datasets with inline annotations. We experimented with our system on several NLP facilitated tasks including computational phenotyping for lymphoma patients and semantic relation extraction for clinical notes. These experiments showcased the broader applicability and utility of LAPNLP.Comment: 6 pages, accepted by IEEE BIBM 2018 as regular pape

Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU

Machine learning approaches have been effective in predicting adverse outcomes in different clinical settings. These models are often developed and evaluated on datasets with heterogeneous patient populations. However, good predictive performance on the aggregate population does not imply good performance for specific groups. In this work, we present a two-step framework to 1) learn relevant patient subgroups, and 2) predict an outcome for separate patient populations in a multi-task framework, where each population is a separate task. We demonstrate how to discover relevant groups in an unsupervised way with a sequence-to-sequence autoencoder. We show that using these groups in a multi-task framework leads to better predictive performance of in-hospital mortality both across groups and overall. We also highlight the need for more granular evaluation of performance when dealing with heterogeneous populations.Comment: KDD 201

LAS: a software platform to support oncological data management

The rapid technological evolution in the biomedical and molecular oncology fields is providing research laboratories with huge amounts of complex and heterogeneous data. Automated systems are needed to manage and analyze this knowledge, allowing the discovery of new information related to tumors and the improvement of medical treatments. This paper presents the Laboratory Assistant Suite (LAS), a software platform with a modular architecture designed to assist researchers throughout diverse laboratory activities. The LAS supports the management and the integration of heterogeneous biomedical data, and provides graphical tools to build complex analyses on integrated data. Furthermore, the LAS interfaces are designed to ease data collection and management even in hostile environments (e.g., in sterile conditions), so as to improve data qualit

Progressive auditory neuropathy in patients with Leber's hereditary optic neuropathy

Objective: To investigate auditory neural involvement in patients with Leber's hereditary optic neuropathy (LHON).Methods: Auditory assessment was undertaken in two patients with LHON. One was a 45 year old woman with Harding disease (multiple-sclerosis-like illness and positive 11778mtDNA mutation) and mild auditory symptoms, whose auditory function was monitored over five years. The other was a 59 year old man with positive 11778mtDNA mutation, who presented with a long standing progressive bilateral hearing loss, moderate on one side and severe to profound on the other. Standard pure tone audiometry, tympanometry, stapedial reflex threshold measurements, stapedial reflex decay, otoacoustic emissions with olivo-cochlear suppression, auditory brain stem responses, and vestibular function tests were undertaken.Results: Both patients had good cochlear function, as judged by otoacoustic emissions ( intact outer hair cells) and normal stapedial reflexes ( intact inner hair cells). A brain stem lesion was excluded by negative findings on imaging, recordable stapedial reflex thresholds, and, in one of the patients, olivocochlear suppression of otoacoustic emissions. The deterioration of auditory function implied a progressive course in both cases. Vestibular function was unaffected.Conclusions: The findings are consistent with auditory neuropathy - a lesion of the cochlear nerve presenting with abnormal auditory brain stem responses and with normal inner hair cells and the cochlear nucleus (lower brain stem). The association of auditory neuropathy, or any other auditory dysfunction, with LHON has not been recognised previously. Further studies are necessary to establish whether this is a consistent finding

Concordance of Genotyping and Phenotyping in the Classification of Methicillin-Resistant Staphylococcus Aureus

Methicillin-resistant Staphylococcus aureus (MRSA) strains have spread in Saudi Arabia, increasing morbidity, mortality, and financial burdens. Recent studies have suggested the phenotyping methods typically used to classify MRSA as either health care MRSA (HA-MRSA) or community-associated MRSA (CA-MRSA) cases are unreliable, because they lack concordance with the results of genotyping. Yet the expense associated with genotyping precludes its use in the Saudi Aramco population in Saudi Arabia. The absence of a standardized and affordable method to classify MRSA into CA-MRSA and HA-MRSA has been a challenge for infection control programs in Saudi Arabia. The objective of this quantitative, secondary data analysis was to determine the most reliable phenotyping approach to strain identification using John Hopkins Aramco hospital data. The ecological and antibiotics selection pressure theories framed this research. The results of concordance, and sensitivity and specificity tests, suggested hospital admission profiles and susceptibility pattern were the most reliable phenotypic predictors of genotype-based classifications. Multiple logistic regression for susceptibility pattern (OR = 15.47, p \u3c .001) and hospital admission profile (OR = 2.87, p = .008) confirmed those results, whereas all other variables were not found to be statistically significant. These results can be used to clarify the epidemiological and molecular factors that affect the transition of MRSA from health care facilities to the Saudi Aramco community. Implications for positive social change include faster and more reliable classification of MRSA to aid in disease surveillance and the selection of appropriate treatments to reduce MRSA-related morbidity and mortality

Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology.

Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype-driven early genetic diagnosis of fetal genetic disease can help to strategize treatment options and clinical preventive measures during the perinatal period, to plan in utero therapies, and to inform parental decision-making. Fetal phenotypes of genetic diseases are often unique and at present are not well understood; more comprehensive knowledge about prenatal phenotypes and computational resources have an enormous potential to improve diagnostics and translational research. The Human Phenotype Ontology (HPO) has been widely used to support diagnostics and translational research in human genetics. To better support prenatal usage, the HPO consortium conducted a series of workshops with a group of domain experts in a variety of medical specialties, diagnostic techniques, as well as diseases and phenotypes related to prenatal medicine, including perinatal pathology, musculoskeletal anomalies, neurology, medical genetics, hydrops fetalis, craniofacial malformations, cardiology, neonatal-perinatal medicine, fetal medicine, placental pathology, prenatal imaging, and bioinformatics. We expanded the representation of prenatal phenotypes in HPO by adding 95 new phenotype terms under the Abnormality of prenatal development or birth (HP:0001197) grouping term, and revised definitions, synonyms, and disease annotations for most of the 152 terms that existed before the beginning of this effort. The expansion of prenatal phenotypes in HPO will support phenotype-driven prenatal exome and genome sequencing for precision genetic diagnostics of rare diseases to support prenatal care

Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology

Human phenotype ontology; Prenatal diagnosis; Prenatal phenotypingOntología del fenotipo humano; Diagnóstico prenatal; Fenotipado prenatalOntologia del fenotip humà; Diagnòstic prenatal; Fenotipat prenatalTechnological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype-driven early genetic diagnosis of fetal genetic disease can help to strategize treatment options and clinical preventive measures during the perinatal period, to plan in utero therapies, and to inform parental decision-making. Fetal phenotypes of genetic diseases are often unique and at present are not well understood; more comprehensive knowledge about prenatal phenotypes and computational resources have an enormous potential to improve diagnostics and translational research. The Human Phenotype Ontology (HPO) has been widely used to support diagnostics and translational research in human genetics. To better support prenatal usage, the HPO consortium conducted a series of workshops with a group of domain experts in a variety of medical specialties, diagnostic techniques, as well as diseases and phenotypes related to prenatal medicine, including perinatal pathology, musculoskeletal anomalies, neurology, medical genetics, hydrops fetalis, craniofacial malformations, cardiology, neonatal-perinatal medicine, fetal medicine, placental pathology, prenatal imaging, and bioinformatics. We expanded the representation of prenatal phenotypes in HPO by adding 95 new phenotype terms under the Abnormality of prenatal development or birth (HP:0001197) grouping term, and revised definitions, synonyms, and disease annotations for most of the 152 terms that existed before the beginning of this effort. The expansion of prenatal phenotypes in HPO will support phenotype-driven prenatal exome and genome sequencing for precision genetic diagnostics of rare diseases to support prenatal care.European Commission; National Human Genome Research Institute; NIH Office of the Director; The European Union's EIT-Health Innovation Program bp2020-2022, Grant/Award Numbers: #211015, #20062; NIH Office of the Director (OD), the European Union's Horizon 2020 research and innovation program, Grant/Award Number: 779257; NHGRI, Grant/Award Numbers: 2R24OD011883-05A1, 1U24HG011449-01A