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1.
Nat Med ; 2020 Jun 22.
Artigo em Inglês | MEDLINE | ID: mdl-32572267

RESUMO

The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human-computer collaboration in clinical practice.

2.
Sci Rep ; 10(1): 10778, 2020 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-32587310

RESUMO

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

3.
Sci Rep ; 10(1): 8140, 2020 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-32424214

RESUMO

Equations predicting the risk of occurrence of cardiovascular disease (CVD) are used in primary care to identify high-risk individuals among the general population. To improve the predictive performance of such equations, we updated the Framingham general CVD 1991 and 2008 equations and the Pooled Cohort equations for atherosclerotic CVD within five years in a contemporary cohort of individuals who participated in the Austrian health-screening program from 2009-2014. The cohort comprised 1.7 M individuals aged 30-79 without documented CVD history. CVD was defined by hospitalization or death from cardiovascular cause. Using baseline and follow-up data, we recalibrated and re-estimated the equations. We evaluated the gain in discrimination and calibration and assessed explained variation. A five-year general CVD risk of 4.61% was observed. As expected, discrimination c-statistics increased only slightly and ranged from 0.73-0.79. The two original Framingham equations overestimated the CVD risk, whereas the original Pooled Cohort equations underestimated it. Re-estimation improved calibration of all equations adequately, especially for high-risk individuals. Half of the individuals were reclassified into another risk category using the re-estimated equations. Predictors in the re-estimated Framingham equations explained 7.37% of the variation, whereas the Pooled Cohort equations explained 5.81%. Age was the most important predictor.

4.
J Med Internet Res ; 22(1): e15597, 2020 01 24.
Artigo em Inglês | MEDLINE | ID: mdl-32012058

RESUMO

BACKGROUND: The diagnosis of pigmented skin lesion is error prone and requires domain-specific expertise, which is not readily available in many parts of the world. Collective intelligence could potentially decrease the error rates of nonexperts. OBJECTIVE: The aim of this study was to evaluate the feasibility and impact of collective intelligence for the detection of skin cancer. METHODS: We created a gamified study platform on a stack of established Web technologies and presented 4216 dermatoscopic images of the most common benign and malignant pigmented skin lesions to 1245 human raters with different levels of experience. Raters were recruited via scientific meetings, mailing lists, and social media posts. Education was self-declared, and domain-specific experience was tested by screening tests. In the target test, the readers had to assign 30 dermatoscopic images to 1 of the 7 disease categories. The readers could repeat the test with different lesions at their own discretion. Collective human intelligence was achieved by sampling answers from multiple readers. The disease category with most votes was regarded as the collective vote per image. RESULTS: We collected 111,019 single ratings, with a mean of 25.2 (SD 18.5) ratings per image. As single raters, nonexperts achieved a lower mean accuracy (58.6%) than experts (68.4%; mean difference=-9.4%; 95% CI -10.74% to -8.1%; P<.001). Collectives of nonexperts achieved higher accuracies than single raters, and the improvement increased with the size of the collective. A collective of 4 nonexperts surpassed single nonexperts in accuracy by 6.3% (95% CI 6.1% to 6.6%; P<.001). The accuracy of a collective of 8 nonexperts was 9.7% higher (95% CI 9.5% to 10.29%; P<.001) than that of single nonexperts, an improvement similar to single experts (P=.73). The sensitivity for malignant images increased for nonexperts (66.3% to 77.6%) and experts (64.6% to 79.4%) for answers given faster than the intrarater mean. CONCLUSIONS: A high number of raters can be attracted by elements of gamification and Web-based marketing via mailing lists and social media. Nonexperts increase their accuracy to expert level when acting as a collective, and faster answers correspond to higher accuracy. This information could be useful in a teledermatology setting.


Assuntos
Inteligência/genética , Neoplasias Cutâneas/diagnóstico , Telemedicina/métodos , Feminino , Humanos , Internet , Masculino , Neoplasias Cutâneas/patologia
5.
Pharmacoepidemiol Drug Saf ; 29(2): 189-198, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31808271

RESUMO

PURPOSE: Overactive bladder (OAB) syndrome has severe effects on quality of life. Certain drugs are known risk factors for OAB but have not been investigated in a population-wide cohort. The objective of this study was to investigate the role of prescription drugs in the etiology of the OAB. METHODS: Retrospective cohort study using a population-wide database of 4 185 098 OAB-naïve women followed Strengthening the Reporting of Observational Studies in Epidemiology guidelines. We investigated the subscription use of anticholinergic medication and 188 chemical substances, which are suspected triggers for OAB (trigger medications [TMs]). We hypothesized a relationship between the prescription for one or more TM and the prescription for anticholinergic medication against OAB (marker medication [MM]). RESULTS: The use of MM in Austria increased from 2009 to 2012 on average by 0.025 percentage points per year (95% confidence interval [CI]: 0.015-0.036). In December 2012, 1 in 123 women filled a prescription for any MM, equaling an average utilization of 0.84%. The relative risk of filling a prescription for a MM 6 months after filling a prescription for a TM was 2.70 (95% CI: 2.64-2.77). All investigated medication classes showed a higher risk for the prescription for MM. Medication from classes "genitourinary system and sex hormones" and "systemic anti-infectives" caused the highest increase in risk (109% and 89%, respectively). Prescriptions for class "cardiovascular system" caused the lowest increase in the risk (15%). CONCLUSION: Certain prescription medications are a significant risk factor for the need to take anticholinergic medication as a consequence.

6.
J Med Syst ; 43(10): 314, 2019 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-31494719

RESUMO

The Main Association of Austrian Social Security Institutions collects pseudonymized claims data from Austrian social security institutions and information about hospital stays in a database for research purposes. For new studies the same data are repeatedly reprocessed and it is difficult to compare different study results even though the data is already preprocessed and prepared in a proprietary data model. Based on a study on adverse drug events in relation to inappropriate medication in geriatric patients the suitability of the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) is analyzed and data is transformed into the OMOP CDM. 1,023 (99.7%) of drug codes and 3,812 (99.2%) of diagnoses codes coincide with the OMOP vocabularies. The biggest obstacles are missing mappings for the Local Vocabularies like the Austrian pharmaceutical registration numbers and the Socio-Economic Index to the OMOP vocabularies. OMOP CDM is a promising approach for the standardization of Austrian claims data. In the long run, the benefits of standardization and reproducibility of research should outweigh this initial drawback.


Assuntos
Bases de Dados Factuais/normas , Revisão da Utilização de Seguros/organização & administração , Idoso , Idoso de 80 Anos ou mais , Áustria/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Estudos de Viabilidade , Geriatria , Humanos , Revisão da Utilização de Seguros/normas , Uso Indevido de Medicamentos sob Prescrição/estatística & dados numéricos , Reprodutibilidade dos Testes , Fatores Socioeconômicos
7.
Lancet Oncol ; 20(7): 938-947, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31201137

RESUMO

BACKGROUND: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human readers for all clinically relevant types of benign and malignant pigmented skin lesions. METHODS: For this open, web-based, international, diagnostic study, human readers were asked to diagnose dermatoscopic images selected randomly in 30-image batches from a test set of 1511 images. The diagnoses from human readers were compared with those of 139 algorithms created by 77 machine-learning labs, who participated in the International Skin Imaging Collaboration 2018 challenge and received a training set of 10 015 images in advance. The ground truth of each lesion fell into one of seven predefined disease categories: intraepithelial carcinoma including actinic keratoses and Bowen's disease; basal cell carcinoma; benign keratinocytic lesions including solar lentigo, seborrheic keratosis and lichen planus-like keratosis; dermatofibroma; melanoma; melanocytic nevus; and vascular lesions. The two main outcomes were the differences in the number of correct specific diagnoses per batch between all human readers and the top three algorithms, and between human experts and the top three algorithms. FINDINGS: Between Aug 4, 2018, and Sept 30, 2018, 511 human readers from 63 countries had at least one attempt in the reader study. 283 (55·4%) of 511 human readers were board-certified dermatologists, 118 (23·1%) were dermatology residents, and 83 (16·2%) were general practitioners. When comparing all human readers with all machine-learning algorithms, the algorithms achieved a mean of 2·01 (95% CI 1·97 to 2·04; p<0·0001) more correct diagnoses (17·91 [SD 3·42] vs 19·92 [4·27]). 27 human experts with more than 10 years of experience achieved a mean of 18·78 (SD 3·15) correct answers, compared with 25·43 (1·95) correct answers for the top three machine algorithms (mean difference 6·65, 95% CI 6·06-7·25; p<0·0001). The difference between human experts and the top three algorithms was significantly lower for images in the test set that were collected from sources not included in the training set (human underperformance of 11·4%, 95% CI 9·9-12·9 vs 3·6%, 0·8-6·3; p<0·0001). INTERPRETATION: State-of-the-art machine-learning classifiers outperformed human experts in the diagnosis of pigmented skin lesions and should have a more important role in clinical practice. However, a possible limitation of these algorithms is their decreased performance for out-of-distribution images, which should be addressed in future research. FUNDING: None.

8.
Stud Health Technol Inform ; 260: 226-233, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31118342

RESUMO

BACKGROUND: Reuse of EHR data for selecting patients who are eligible for clinical research can substantially improve the recruitment process. ART-DECOR is an open-source tool that is commonly used to design and publish HL7 V3 templates of national (e.g. ELGA) and international EHR initiatives. OBJECTIVES: Extend ART-DECOR to allow the definition of criteria that may be used for patient selection. METHODS: Using the native ART-DECOR development framework we extended existing ART-DECOR template associations by allowing conditions to be formulated. RESULTS: An editor for the specification of conditions was implemented. The resulting criteria are internally translated to XPath expressions and can be immediately applied to CDA documents. As a prototypical application of our approach we implemented a "Trial Criteria Evaluator" tool that allows trial eligibility criteria to be composed of our ART-DECOR criteria and have them checked against a patient's CDA documents. CONCLUSION: Referring to HL7 templates, our criteria can be applied to documents of national EHR systems such as ELGA and hereby reach a broad patient cohort. Implementing our approach within ART-DECOR alleviates its reuse and enhancement by other researchers.


Assuntos
Registros Eletrônicos de Saúde , Seleção de Pacientes , Vocabulário Controlado , Assistência à Saúde , Humanos
9.
JMIR Med Inform ; 7(2): e12172, 2019 Apr 12.
Artigo em Inglês | MEDLINE | ID: mdl-30977733

RESUMO

BACKGROUND: Health information exchange (HIE) among care providers who cooperate in the treatment of patients with diabetes mellitus (DM) has been rated as an important aspect of successful care. Patient-sharing relations among care providers permit inferences about corresponding information-sharing relations. OBJECTIVES: This study aimed to obtain information for an effective HIE platform design to be used in DM care by analyzing patient-sharing relations among various types of care providers (ToCPs), such as hospitals, pharmacies, and different outpatient specialists, within a nationwide claims dataset of Austrian DM patients. We focus on 2 parameters derived from patient-sharing networks: (1) the principal HIE partners of the different ToCPs involved in the treatment of DM and (2) the required participation rate of ToCPs in HIE platforms for the purpose of effective communication. METHODS: The claims data of 7.9 million Austrian patients from 2006 to 2007 served as our data source. DM patients were identified by their medication. We established metrics for the quantification of our 2 parameters of interest. The principal HIE partners were derived from the portions of a care provider's patient-sharing relations with different ToCPs. For the required participation rate of ToCPs in an HIE platform, we determine the concentration of patient-sharing relations among ToCPs. Our corresponding metrics are derived in analogy from existing work for the quantification of the continuity of care. RESULTS: We identified 324,703 DM patients treated by 12,226 care providers; the latter were members of 16 ToCPs. On the basis of their score for 2 of our parameters, we categorized the ToCPs into low, medium, and high. For the most important HIE partner parameter, pharmacies, general practitioners (GPs), and laboratories were the representatives of the top group, that is, our care providers shared the highest numbers of DM patients with these ToCPs. For the required participation rate of type of care provide (ToCP) in HIE platform parameter, the concentration of DM patient-sharing relations with a ToCP tended to be inversely related to the ToCPs member count. CONCLUSIONS: We conclude that GPs, pharmacies, and laboratories should be core members of any HIE platform that supports DM care, as they are the most important DM patient-sharing partners. We further conclude that, for implementing HIE with ToCPs who have many members (in Austria, particularly GPs and pharmacies), an HIE solution with high participation rates from these ToCPs (ideally a nationwide HIE platform with obligatory participation of the concerned ToCPs) seems essential. This will raise the probability of HIE being achieved with any care provider of these ToCPs. As chronic diseases are rising because of aging societies, we believe that our quantification of HIE requirements in the treatment of DM can provide valuable insights for many industrial countries.

10.
Stud Health Technol Inform ; 258: 151-152, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30942734

RESUMO

The suitability of the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) for Austrian pseudonymized claims data from social security institutions and information about hospital stays is evaluated. 1,023 (99.7%) of ATC codes and 3,695 (98.6%) of ICD10 codes coincide with the OMOP vocabulary. Mappings for the local vocabularies like the Austrian pharmaceutical registration numbers, the Socio-Economic Index and professional groups, to the OMOP vocabulary do not exist. A standardization with the OMOP CDM is possible, however an initial, not negligible effort is required to adapt and incorporate the vocabulary.


Assuntos
Análise de Dados , Revisão da Utilização de Seguros , Modelos Estatísticos , Áustria , Bases de Dados Factuais , Estudos de Viabilidade
11.
JAMA Dermatol ; 155(1): 58-65, 2019 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30484822

RESUMO

Importance: Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose. Objective: To compare the accuracy of a CNN-based classifier with that of physicians with different levels of experience. Design, Setting, and Participants: A CNN-based classification model was trained on 7895 dermoscopic and 5829 close-up images of lesions excised at a primary skin cancer clinic between January 1, 2008, and July 13, 2017, for a combined evaluation of both imaging methods. The combined CNN (cCNN) was tested on a set of 2072 unknown cases and compared with results from 95 human raters who were medical personnel, including 62 board-certified dermatologists, with different experience in dermoscopy. Main Outcomes and Measures: The proportions of correct specific diagnoses and the accuracy to differentiate between benign and malignant lesions measured as an area under the receiver operating characteristic curve served as main outcome measures. Results: Among 95 human raters (51.6% female; mean age, 43.4 years; 95% CI, 41.0-45.7 years), the participants were divided into 3 groups (according to years of experience with dermoscopy): beginner raters (<3 years), intermediate raters (3-10 years), or expert raters (>10 years). The area under the receiver operating characteristic curve of the trained cCNN was higher than human ratings (0.742; 95% CI, 0.729-0.755 vs 0.695; 95% CI, 0.676-0.713; P < .001). The specificity was fixed at the mean level of human raters (51.3%), and therefore the sensitivity of the cCNN (80.5%; 95% CI, 79.0%-82.1%) was higher than that of human raters (77.6%; 95% CI, 74.7%-80.5%). The cCNN achieved a higher percentage of correct specific diagnoses compared with human raters (37.6%; 95% CI, 36.6%-38.4% vs 33.5%; 95% CI, 31.5%-35.6%; P = .001) but not compared with experts (37.3%; 95% CI, 35.7%-38.8% vs 40.0%; 95% CI, 37.0%-43.0%; P = .18). Conclusions and Relevance: Neural networks are able to classify dermoscopic and close-up images of nonpigmented lesions as accurately as human experts in an experimental setting.


Assuntos
Algoritmos , Dermoscopia/métodos , Redes Neurais de Computação , Neoplasias Cutâneas/patologia , Adulto , Diagnóstico Diferencial , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Curva ROC , Reprodutibilidade dos Testes , Estudos Retrospectivos , Pele/patologia
12.
Int J Cardiol ; 283: 165-170, 2019 05 15.
Artigo em Inglês | MEDLINE | ID: mdl-30429082

RESUMO

BACKGROUND: Cardiovascular prevention guidelines advocate the use of statistical risk equations to predict individual cardiovascular risk. However, predictive accuracy and clinical value of existing equations may differ in populations other than the one used for their development. Using baseline and follow-up data of the Austrian health-screening program, we assessed discrimination, calibration, and clinical utility of three widely recommended equations-the Framingham 1991 and 2008 general cardiovascular disease (CVD) equations, and the Pooled Cohort equations predicting atherosclerotic CVD. METHODS: The validation cohort comprised 1.7 M individuals aged 30-79, without documented CVD history who participated in the program from 2009 to 2014. CVD events were defined by a cardiovascular cause of hospitalization or death. RESULTS: The observed five-year general CVD risk was 4.66%. Discrimination c-indices (0.72-0.78) were slightly lower than those reported for the development cohorts. C-indices for women were always higher than for men. CVD risk was overestimated by the Framingham 2008 equation, but underestimated by the Pooled Cohort equations. The Framingham 1991 equation was well-calibrated, especially for individuals up to 64 years. If applied to recommend health interventions at a predicted five-year risk between 5 and 10%, the equations were clinically useful with their net benefits, weighting true positives against false positives, ranging from 0.13 to 3.43%. CONCLUSION: The equations can discriminate high-risk from low-risk individuals, but predictive accuracy (especially for high-risk individuals) might be improved by recalibration. The Framingham 1991 equation yielded the most accurate predictions.


Assuntos
Doenças Cardiovasculares/epidemiologia , Sistema de Registros , Medição de Risco/métodos , Adulto , Idoso , Áustria/epidemiologia , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Fatores de Risco , Distribuição por Sexo , Taxa de Sobrevida/tendências
13.
Artigo em Inglês | MEDLINE | ID: mdl-30544735

RESUMO

BACKGROUND: Process mining is a relatively new discipline that helps to discover and analyze actual process executions based on log data. In this paper we apply conformance checking techniques to the process of surveillance of melanoma patients. This process consists of recurring events with time constraints between the events. OBJECTIVES: The goal of this work is to show how existing clinical data collected during melanoma surveillance can be prepared and pre-processed to be reused for process mining. METHODS: We describe an approach based on time boxing to create process models from medical guidelines and the corresponding event logs from clinical data of patient visits. RESULTS: Event logs were extracted for 1023 patients starting melanoma surveillance at the Department of Dermatology at the Medical University of Vienna between January 2010 and June 2017. Conformance checking techniques available in the ProM framework and explorative applied process mining techniques were applied. CONCLUSIONS: The presented time boxing enables the direct use of existing process mining frameworks like ProM to perform process-oriented analysis also with respect to time constraints between events.


Assuntos
Mineração de Dados/métodos , Assistência à Saúde/estatística & dados numéricos , Monitoramento Epidemiológico , Vigilância da População , Adulto , Idoso , Áustria , Feminino , Humanos , Masculino , Melanoma , Pessoa de Meia-Idade
14.
Clin Respir J ; 12(12): 2627-2634, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30276967

RESUMO

INTRODUCTION: Beta-blockers are indicated for secondary prevention of coronary artery disease (CAD). However, in patients with co-morbidity of chronic obstructive pulmonary disease (COPD) an underuse of beta-blocker has been reported. MATERIALS AND METHODS: Prescription and demographic data and information on hospital discharge diagnoses from 13 Austrian health insurance funds for the years 2006-2007 were analyzed. The primary end point was all-cause mortality of patients with CAD with or without COPD and its association with use of beta-blockers. RESULTS: In 2006 and 2007, 65717 patients (37% female, 63% male) were discharged with a diagnosis of CAD. Among these patients, 46% had a co-diagnosis of COPD, 24% had diabetes, and 75% received beta-blockers. Use of beta-blockers was comparable in CAD patients with COPD and without COPD with 77% and 74%, respectively. Thousand eight hundred seventy-two (8.1%) and 1473 (5.6%) patients with and without COPD, who used beta-blockers died within months in 2006 and 2007. Thousand five hundred fifty-three (22.0%) and 1862 (22.2%) of patients with and without COPD and without beta-blockers died during the corresponding time period. DISCUSSION: Use of beta-blockers was similar in patients with CAD with or without co-diagnosis of COPD. However, mortality of beta-blocker users was markedly lower than that of nonusers in patients with CAD with or without COPD.


Assuntos
Antagonistas Adrenérgicos beta/uso terapêutico , Doença da Artéria Coronariana/tratamento farmacológico , Uso de Medicamentos/estatística & dados numéricos , Doença Pulmonar Obstrutiva Crônica/tratamento farmacológico , Adolescente , Antagonistas Adrenérgicos beta/administração & dosagem , Adulto , Idoso , Idoso de 80 Anos ou mais , Áustria/epidemiologia , Comorbidade , Doença da Artéria Coronariana/epidemiologia , Doença da Artéria Coronariana/mortalidade , Doença da Artéria Coronariana/prevenção & controle , Uso de Medicamentos/tendências , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Doença Pulmonar Obstrutiva Crônica/diagnóstico , Doença Pulmonar Obstrutiva Crônica/epidemiologia , Doença Pulmonar Obstrutiva Crônica/mortalidade , Estudos Retrospectivos , Fatores de Risco , Prevenção Secundária , Análise de Sobrevida , Adulto Jovem
15.
Stud Health Technol Inform ; 248: 94-99, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29726424

RESUMO

BACKGROUND: To develop simulation models for healthcare related questions clinical data can be reused. OBJECTIVES: Develop a clinical data warehouse to harmonize different data sources in a standardized manner and get a reproducible interface for clinical data reuse. METHODS: The Kimball life cycle for the development of data warehouse was used. The development is split into the technical, the data and the business intelligence pathway. RESULTS: Sample data was persisted in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The i2b2 clinical data warehouse tools were used to query the OMOP CDM by applying the new i2b2 multi-fact table feature. CONCLUSION: A clinical data warehouse was set up and sample data, data dimensions and ontologies for Austrian health claims data were created. The ability of the standardized data access layer to create and apply simulation models will be evaluated next.


Assuntos
Data Warehousing , Bases de Dados Factuais , Armazenamento e Recuperação da Informação , Áustria , Assistência à Saúde , Humanos
16.
Stud Health Technol Inform ; 247: 850-854, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29678081

RESUMO

Medical terms of anatomical regions are not sufficient to unequivocally describe the locations of lesions on the skin. In order to get gender, age, height and weight independent localisations on the human skin we propose to use the base mesh of MakeHuman in combination with UV coordinates. As proof-of-concept we present a web application based on Three.js with three different MakeHuman 3D models (male, female, infant). Anatomical regions corresponding to UV coordinates are displayed and the UV coordinates of skin lesions can be marked. Marked regions are "transformed" to changed 3D models automatically allowing for tracking in spite of anatomic changes.


Assuntos
Imageamento Tridimensional , Dermatopatias , Pele , Feminino , Humanos , Masculino , Modelos Anatômicos
17.
J Am Acad Dermatol ; 77(6): 1100-1109, 2017 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-28941871

RESUMO

BACKGROUND: Nonpigmented skin cancer is common, and diagnosis with the unaided eye is error prone. OBJECTIVE: To investigate whether dermatoscopy improves the diagnostic accuracy for nonpigmented (amelanotic) cutaneous neoplasms. METHODS: We collected a sample of 2072 benign and malignant neoplastic lesions and inflammatory conditions and presented close-up images taken with and without dermatoscopy to 95 examiners with different levels of experience. RESULTS: The area under the curve was significantly higher with than without dermatoscopy (0.68 vs 0.64, P < .001). Among 51 possible diagnoses, the correct diagnosis was selected in 33.1% of cases with and 26.4% of cases without dermatoscopy (P < .001). For experts, the frequencies of correct specific diagnoses of a malignant lesion improved from 40.2% without to 51.3% with dermatoscopy. For all malignant neoplasms combined, the frequencies of appropriate management strategies increased from 78.1% without to 82.5% with dermatoscopy. LIMITATIONS: The study deviated from a real-life clinical setting and was potentially affected by verification and selection bias. CONCLUSIONS: Dermatoscopy improves the diagnosis and management of nonpigmented skin cancer and should be used as an adjunct to examination with the unaided eye.


Assuntos
Dermoscopia , Neoplasias Cutâneas/patologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Reprodutibilidade dos Testes , Adulto Jovem
18.
J Dtsch Dermatol Ges ; 15(5): 517-523, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28485868

RESUMO

HINTERGRUND UND ZIELE: Wir untersuchten den Nutzen der sequentiellen digitalen Dermatoskopie für die Kontrolle von Patienten mit multiplen Nävi in einem spezialisierten Zentrum. PATIENTEN UND METHODIK: Das ist eine retrospektive Kohortenstudie mit 2 824 Patienten und 23 241 kontrollierten Läsionen, wobei für Schlüsselparameter, wie der Anzahl der kontrollierten und exzidierten Melanome und Nävi, eine Trendberechnung durchgeführt wurde. ERGEBNISSE: Im Zuge der Kontrolluntersuchungen haben wir bei 709 Patienten 1 266 Läsionen exzidiert, darunter waren 146 (11,5 %) Melanome. Der Anteil der im Zuge der Kontrolle detektierten in-situ-Melanome war signifikant höher als bei der Erstuntersuchung. (46,6 % gegenüber 23,4 %; p ≤ 0,001). Bei Patienten mit einem Melanom bei der Erstuntersuchung war das Risiko, während der Nachsorge ein Melanom zu detektieren, höher als bei Patienten ohne Melanom (relatives Risiko: 3,59; 95 % CI: 2,15 bis 6,00). Die Zahl der dokumentierten Läsionen korrelierte positiv mit dem Verhältnis von gutartigen zu bösartigen excidierten Läsionen und die Exzisionen bei Erstuntersuchungen gingen während des Untersuchungszeitraums signifikant zurück. SCHLUSSFOLGERUNGEN: Die Überwachung mit digitaler Dermatoskopie verbessert die Detektion dünner Melanome bei Patienten mit multiplen Nävi. Patienten mit einem Melanom im Rahmen der Erstuntersuchung haben ein erhöhtes Risiko, während der Nachsorge ein Melanom zu entwickeln und sollten daher eine Zielgruppe für die sequentielle Dermatoskopie sein.

19.
J Dtsch Dermatol Ges ; 15(5): 517-522, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28485882

RESUMO

BACKGROUND AND OBJECTIVES: We examined the value of monitoring patients with multiple nevi using sequential digital dermatoscopy imaging at a tertiary referral center. PATIENTS AND METHODS: This is a retrospective cohort study including 2,824 patients and 23,241 monitored lesions. We calculated trends in key parameters such as the number of melanomas and nevi monitored and excised. RESULTS: During follow-up, we excised 1,266 lesions in 709 patients, including 146 (11.5 %) melanomas. The percentage of in situ melanomas detected at follow-up was significantly higher than at baseline (46.6 % versus 23.4 %, p ≤ 0.001). The risk of detecting a melanoma during follow-up was higher for patients with a melanoma at baseline, compared to those without (relative risk: 3.59, 95 % CI: 2.15 to 6.00). The number of documented lesions showed a positive correlation with the benign/malignant ratio, and excisions at baseline decreased significantly over the course of the study period. CONCLUSION: Digital dermatoscopy monitoring improves the detection of thin melanomas in patients with multiple nevi. Patients with a melanoma at baseline are at an increased risk of developing a melanoma during follow-up and should therefore be a target group for sequential dermatoscopy imaging.


Assuntos
Dermoscopia/estatística & dados numéricos , Interpretação de Imagem Assistida por Computador/métodos , Nevo/diagnóstico por imagem , Nevo/cirurgia , Neoplasias Cutâneas/diagnóstico por imagem , Neoplasias Cutâneas/cirurgia , Adulto , Áustria/epidemiologia , Dermoscopia/métodos , Feminino , Humanos , Estudos Longitudinais , Masculino , Nevo/epidemiologia , Prevalência , Encaminhamento e Consulta/estatística & dados numéricos , Reprodutibilidade dos Testes , Medição de Risco , Sensibilidade e Especificidade , Vigilância de Evento Sentinela , Processamento de Sinais Assistido por Computador , Neoplasias Cutâneas/epidemiologia , Centros de Atenção Terciária/estatística & dados numéricos
20.
Stud Health Technol Inform ; 236: 204-210, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28508797

RESUMO

BACKGROUND: Data from the health care domain is often reused to create and parameterize simulation models for example to support life science business in the evaluation of new products. Data quality assessments play an important part to help model users in interpreting simulation results by showing deficiencies in the raw data used in the model building and offers model builders a comparison of data quality amongst the used data assets. OBJECTIVES: Assess data quality in raw data prior to creating simulation models and prepare results for model users. METHODS: Using a literature review and documentation of previous models created, we searched data quality criteria. For eligible criteria we formulated questions and viable answers to be used in a questionnaire to assess data quality of a data asset. RESULTS: We developed a web tool to evaluate data assets using a generic data model. Percentage results are visualized using a radar chart. CONCLUSION: Data quality assessment with questionnaires offers model builders a framework to critically analyse raw data and to detect deficiencies early in the modelling process. The summarized results can help model users to better interpret simulation results.


Assuntos
Confiabilidade dos Dados , Internet , Informática Médica , Humanos , Inquéritos e Questionários
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