Research in progress: report on the ICAIL 2017 doctoral consortium

This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences

Management of obstructive sleep apnea in Europe-A 10-year follow-up

Objective: In 2010, a questionnaire-based study on obstructive sleep apnea (OSA) management in Europe identified differences regarding reimbursement, sleep specialist qualification, and titration procedures. Now, 10 years later, a follow-up study was conducted as part of the ESADA (European Sleep Apnea Database) network to explore the development of OSA management over time.Methods: The 2010 questionnaire including questions on sleep diagnostic, reimbursement, treatment, and certification was updated with questions on telemedicine and distributed to European Sleep Centers to reflect European OSA management practice.Results: 26 countries (36 sleep centers) participated, representing 20 ESADA and 6 non-ESADA countries. All 21 countries from the 2010 survey participated. In 2010, OSA diagnostic procedures were performed mainly by specialized physicians (86%), whereas now mainly by certified sleep specialists and specialized physicians (69%). Treatment and titration procedures are currently quite homogenous, with a strong trend towards more Autotitrating Positive Airway Pressure treatment (in hospital 73%, at home 62%). From 2010 to 2020, home sleep apnea testing use increased (76%-89%) and polysomnography as sole diagnostic procedure decreased (24%-12%). Availability of a sleep specialist qualification increased (52%-65%) as well as the number of certified polysomnography scorers (certified physicians: 36%-79%; certified technicians: 20%-62%). Telemedicine, not surveyed in 2010, is now in 2020 used in diagnostics (8%), treatment (50%), and follow-up (73%). Conclusion: In the past decade, formal qualification of sleep center personnel increased, OSA diagnostic and treatment procedures shifted towards a more automatic approach, and telemedicine became more prominent.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Management of obstructive sleep apnea in Europe – A 10-year follow-up

Funding Information: Sleep medicine has been further established and recognized in the past 10 years. This is also shown by the fact that sleep-related diseases may receive a separate chapter in the new ICD-11 (International Classification of Diseases 11th Revision) [11]. However, the initial expansion in sleep laboratories and sleep centers seems to be over, at least in Europe, which stands in contradiction to the growing need. While sleep medical care still seems to be secured by the established structures, the gap between the increasing need and existing structures is still widening [ 12–14]. There is a lack of sleep medicine specialists, new outpatient structures, and new billing models with the sponsoring institutions. Approaches to solve these problems include the establishment and expansion of home sleep apnea testing (HSAT) [15] and telemedicine-based technologies in the diagnosis and treatment of OSA [16,17]. Telemedicine found its way into sleep medicine around 10 years ago [ 18–20]. One of the very first approaches as early as 1994 used a telephone circuit and a computer-controlled support system to improve OSA treatment by improving lifestyle through tele-guidance on nutrition and exercise [21]. Publisher Copyright: © 2022 The Authors Copyright © 2022 Elsevier B.V. All rights reserved.Objective: In 2010, a questionnaire-based study on obstructive sleep apnea (OSA) management in Europe identified differences regarding reimbursement, sleep specialist qualification, and titration procedures. Now, 10 years later, a follow-up study was conducted as part of the ESADA (European Sleep Apnea Database) network to explore the development of OSA management over time. Methods: The 2010 questionnaire including questions on sleep diagnostic, reimbursement, treatment, and certification was updated with questions on telemedicine and distributed to European Sleep Centers to reflect European OSA management practice. Results: 26 countries (36 sleep centers) participated, representing 20 ESADA and 6 non-ESADA countries. All 21 countries from the 2010 survey participated. In 2010, OSA diagnostic procedures were performed mainly by specialized physicians (86%), whereas now mainly by certified sleep specialists and specialized physicians (69%). Treatment and titration procedures are currently quite homogenous, with a strong trend towards more Autotitrating Positive Airway Pressure treatment (in hospital 73%, at home 62%). From 2010 to 2020, home sleep apnea testing use increased (76%–89%) and polysomnography as sole diagnostic procedure decreased (24%–12%). Availability of a sleep specialist qualification increased (52%–65%) as well as the number of certified polysomnography scorers (certified physicians: 36%–79%; certified technicians: 20%–62%). Telemedicine, not surveyed in 2010, is now in 2020 used in diagnostics (8%), treatment (50%), and follow-up (73%). Conclusion: In the past decade, formal qualification of sleep center personnel increased, OSA diagnostic and treatment procedures shifted towards a more automatic approach, and telemedicine became more prominent.Peer reviewe

Machine learning for classification of hypertension subtypes using multi-omics: a multi-centre, retrospective, data-driven study

Background: Arterial hypertension is a major cardiovascular risk factor. Identification of secondary hypertension in its various forms is key to preventing and targeting treatment of cardiovascular complications. Simplified diagnostic tests are urgently required to distinguish primary and secondary hypertension to address the current underdiagnosis of the latter. Methods: This study uses Machine Learning (ML) to classify subtypes of endocrine hypertension (EHT) in a large cohort of hypertensive patients using multidimensional omics analysis of plasma and urine samples. We measured 409 multi-omics (MOmics) features including plasma miRNAs (PmiRNA: 173), plasma catechol O-methylated metabolites (PMetas: 4), plasma steroids (PSteroids: 16), urinary steroid metabolites (USteroids: 27), and plasma small metabolites (PSmallMB: 189) in primary hypertension (PHT) patients, EHT patients with either primary aldosteronism (PA), pheochromocytoma/functional paraganglioma (PPGL) or Cushing syndrome (CS) and normotensive volunteers (NV). Biomarker discovery involved selection of disease combination, outlier handling, feature reduction, 8 ML classifiers, class balancing and consideration of different age- and sex-based scenarios. Classifications were evaluated using balanced accuracy, sensitivity, specificity, AUC, F1, and Kappa score. Findings: Complete clinical and biological datasets were generated from 307 subjects (PA=113, PPGL=88, CS=41 and PHT=112). The random forest classifier provided ∼92% balanced accuracy (∼11% improvement on the best mono-omics classifier), with 96% specificity and 0.95 AUC to distinguish one of the four conditions in multi-class ALL-ALL comparisons (PPGL vs PA vs CS vs PHT) on an unseen test set, using 57 MOmics features. For discrimination of EHT (PA + PPGL + CS) vs PHT, the simple logistic classifier achieved 0.96 AUC with 90% sensitivity, and ∼86% specificity, using 37 MOmics features. One PmiRNA (hsa-miR-15a-5p) and two PSmallMB (C9 and PC ae C38:1) features were found to be most discriminating for all disease combinations. Overall, the MOmics-based classifiers were able to provide better classification performance in comparison to mono-omics classifiers. Interpretation: We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating administration of appropriate treatment. Funding: European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 633983, Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE (to Z.E. and F.B.), and Deutsche Forschungsgemeinschaft (CRC/Transregio 205/1)

Cross-linguistic neuroimaging and dyslexia: A critical view

Contains fulltext : 90112.pdf ( ) (Closed access)Recent neuro cognitive theories of dyslexia presume that all dyslexics have the same type of brain abnormality irrespective of the particular writing system their language uses In this article we indicate how this presumption is inconsistent with cross linguistic investigations of reading and dyslexia There are two main issues First the information processing requirements of reading vary greatly across different orthographies Second it is known that even within a single orthography there are different subtypes of dyslexia Consequentially it cannot be the case not even within a single orthography let alone across orthographies that all dyslexics have the same type of brain abnormality Neuro cognitive theorizing about dyslexia cannot afford to ignore these issue

Multilingual processing in the brain

Item does not contain fulltextIn this paper, in contrast to previous neuroimaging literature reviews on first language (L1) and second language (L2), the focus was only on neuroimaging studies that were directly conducted on multilingual participants. In total, 14 neuroimaging studies were included in our study such as 10 functional magnetic resonance imaging, 1 positron emission tomography, 2 magneto ncephalography and 1 electroencephalography. Surprisingly, not many neuroimaging studies have been conducted on multilingual participants to date. As a result, most conclusions that are drawn about multilingual processing are in fact solely based on bilingual processing. Moreover, the few multilingual studies that were conducted frequently showed serious methodological flaws, often due to the practical limitations in terms of accessing a large homogeneous multilingual group. In future research, more multilingual neuroimaging studies are needed, in which factors such as language proficiency, age and manner of acquisition, language exposure and linguistic distance between the spoken languages, are better controlled for. Currently, these factors can explain away a large part of the differences that are found in brain activation between L1, L2 and L3. Finally, there is a need for more sophisticated neuroimaging techniques in order to capture non-invasive activity

Partial sleep restriction decreases insulin sensitivity in type 1 diabetes

OBJECTIVE: Sleep restriction results in decreased insulin sensitivity and glucose tolerance in healthy subjects. We hypothesized that sleep duration is also a determinant of insulin sensitivity in patients with type 1 diabetes. RESEARCH DESIGN AND METHODS: We studied seven patients (three men, four women) with type 1 diabetes: mean age 44 +/- 7 years, BMI 23.5 +/- 0.9 kg/m(2), and A1C 7.6 +/- 0.3%. They were studied once after a night of normal sleep duration and once after a night of only 4 h of sleep. Sleep characteristics were assessed by polysomnography. Insulin sensitivity was measured by hyperinsulinemic euglycemic clamp studies with an infusion of [6,6-(2)H(2)]glucose. RESULTS Sleep duration was shorter in the night with sleep restriction than in the unrestricted night (469 +/- 8.5 vs. 222 +/- 7.1 min, P = 0.02). Sleep restriction did not affect basal levels of glucose, nonesterified fatty acids (NEFAs), or endogenous glucose production. Endogenous glucose production during the hyperinsulinemic clamp was not altered during the night of sleep restriction compared with the night of unrestricted sleep (6.2 +/- 0.8 vs. 6.9 +/- 0.6 micromol x kg lean body mass(-1) x min(-1), NS). In contrast, sleep restriction decreased the glucose disposal rate during the clamp (25.5 +/- 2.6 vs. 22.0 +/- 2.1 micromol x kg lean body mass(-1) x min(-1), P = 0.04), reflecting decreased peripheral insulin sensitivity. Accordingly, sleep restriction decreased the rate of glucose infusion by approximately 21% (P = 0.04). Sleep restriction did not alter plasma NEFA levels during the clamp (143 +/- 29 vs. 133 +/- 29 micromol/l, NS). CONCLUSIONS: Partial sleep deprivation during a single night induces peripheral insulin resistance in these seven patients with type 1 diabetes. Therefore, sleep duration is a determinant of insulin sensitivity in patients with type 1 diabetes.Pathogenesis and treatment of chronic pulmonary disease