Augmenting Medical Decision Making With Text-Based Search of Teaching File Repositories and Medical Ontologies

2018 ◽  
Vol 8 (2) ◽  
pp. 18-43 ◽  
Author(s):  
Priya Deshpande ◽  
Alexander Rasin ◽  
Eli T Brown ◽  
Jacob Furst ◽  
Steven M. Montner ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Medical Decision ◽  
Diagnostic Process ◽  
Snomed Ct ◽  
Multiple Sources ◽  
Secondary Sources ◽  
Public Data ◽  
Teaching Files ◽  
Teaching Cases ◽  
Radiology Image

Teaching files are widely used by radiologists in the diagnostic process and for student education. Most hospitals maintain an active collection of teaching files for internal purposes, but many teaching files are also publicly available online, some linked to secondary sources. However, public sources offer very limited (and ad-hoc) search capabilities. Based on the previous work on data integration and text-based search, the authors extended their Integrated Radiology Image Search (IRIS 1.1) engine with a new medical ontology, SNOMED CT, and the ICD10 dictionary. IRIS 1.1 integrates public data sources and applies query expansion with exact and partial matches to find relevant teaching files. Using a set of 28 representative queries from multiple sources, the search engine finds more relevant teaching cases versus other publicly available search engines.

Benefits and limitations of laboratory diagnostic pathways

Diagnosis ◽  
2014 ◽  
Vol 1 (4) ◽  
pp. 269-276 ◽  
Author(s):  
Georg Hoffmann ◽  
Johannes Aufenanger ◽  
Manuela Födinger ◽  
Janne Cadamuro ◽  
Arnold von Eckardstein ◽  
...  
Keyword(s):  
Clinical Pathways ◽  
Logical Consequence ◽  
Point Of View ◽  
Medical Decision ◽  
Diagnostic Process ◽  
Major Drawback ◽  
Economic Point ◽  
Medical Needs ◽  
The One ◽  
Diagnostic Pathways

AbstractDiagnostic pathways are an essential subset of clinical pathways and a logical consequence of DRG-based reimbursement. They combine the principle of stepwise reflex and reflective testing with a management concept that helps to fulfill medical needs with organizational and economic efficacy. The two most common formats describing diagnostic pathways are graphical decision trees on paper and “if…then…else” rules on computers. From a laboratory point of view, diagnostic pathways represent “smart” test profiles, which – in contrast to conventional (inflexible) profiles – are not necessarily worked off completely, but just to a point, where a diagnostic decision can be made. This improves the cost-effectiveness of laboratory testing, while making sure that no essential tests are missed. The paper describes benefits and limitations of diagnostic pathways from a medical, organizational, and economic point of view. Their major advantage is also their major drawback, since they make the diagnostic process on the one hand extremely straight-forward and transparent, while on the other hand oversimplifying the underlying medical decision principles. This may provoke the abuse of their primarily medical intentions for mere economic purposes.

Key Determinants of Successful Implementation of IT in International Commercial Bank

2011 ◽  
pp. 130-154
Author(s):  
Tarek Hatem ◽  
Elham Metwally
Keyword(s):  
Commercial Bank ◽  
Value Chain ◽  
Management Practices ◽  
Single Case ◽  
Successful Implementation ◽  
Multiple Sources ◽  
Related Factors ◽  
Secondary Sources ◽  
It Implementation ◽  
Cultural Pattern

This research reports the results of a single case study that covers a successful project of IT implementation in International Commercial Bank (ICB) from the Egyptian banking industry. The case highlights leadership actions, as well as other related factors regarding effectiveness of IT implementation that are linked to strategic competitiveness and value creation. Multiple sources of data were used. Primary sources include in-depth interviews in semi-structured format with industry authorities, IT and retail banking managers, and the bank’s executives in general; whereas, secondary sources of data include annual reports, website information, and financial statements. Findings show that successful implementation was influenced by the interplay of several management practices, which eventually, had an impact on strategic competitiveness through their impact on some in-house attributes; notably, a dominating constructive cultural pattern leading to higher levels of organizational commitment, and the bank’s value chain.

scholarly journals Towards an App to Estimate Patient-Specific Perioperative Femur Fracture Risk

2020 ◽  
Vol 10 (18) ◽  
pp. 6409 ◽  
Author(s):  
L. Esposito ◽  
V. Minutolo ◽  
P. Gargiulo ◽  
H. Jonsson ◽  
M. K. Gislason ◽  
...  
Keyword(s):  
Decision Making ◽  
Fracture Risk ◽  
Ad Hoc ◽  
Strength Distribution ◽  
Bone Diseases ◽  
Medical Decision ◽  
Patient Specific ◽  
Decision Making Process ◽  
Geometrical Parameters ◽  
Traffic Light

Total Hip Arthroplasty has been one of the most successful surgical procedure in terms of patient outcomes and satisfaction. However, due to increase in life expectancy and the related incidence of age-dependent bone diseases, a growing number of cases of intra-operative fractures lead to revision surgery with high rates of morbidity and mortality. Surgeons choose the type of the implant, either cemented or cementless prosthesis, on the basis of the age, the quality of the bone and the general medical conditions of the patients. Generally, no quantitative measures are available to assess the intra-operative fracture risk. Consequently, the decision-making process is mainly based on surgical operators’ expertise and qualitative information obtained from imaging. Motivated by this scenario, we here propose a mechanical-supported strategy to assist surgeons in their decisions, by giving intelligible maps of the risk fracture which take into account the interplay between the actual mechanical strength distribution inside the bone tissue and its response to the forces exerted by the implant. In the presented study, we produce charts and patient-specific synthetic “traffic-light” indicators of fracture risk, by making use of ad hoc analytical solutions to predict the stress levels in the bone by means of Computed Tomography-based mechanical and geometrical parameters of the patient. We felt that if implemented in a friendly software or proposed as an app, the strategy could constitute a practical tool to help the medical decision-making process, in particular with respect to the choice of adopting cemented or cementless implant.

scholarly journals Passive seismic event estimation using multiscattering waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. KS59-KS69 ◽  
Author(s):  
Chao Song ◽  
Zedong Wu ◽  
Tariq Alkhalifah
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Source Image ◽  
Time Inversion ◽  
Multiple Sources ◽  
Origin Time ◽  
Secondary Sources ◽  
Velocity Models ◽  
Passive Seismic

Passive seismic monitoring has become an effective method to understand underground processes. Time-reversal-based methods are often used to locate passive seismic events directly. However, these kinds of methods are strongly dependent on the accuracy of the velocity model. Full-waveform inversion (FWI) has been used on passive seismic data to invert the velocity model and source image, simultaneously. However, waveform inversion of passive seismic data uses mainly the transmission energy, which results in poor illumination and low resolution. We developed a waveform inversion using multiscattered energy for passive seismic to extract more information from the data than conventional FWI. Using transmission wavepath information from single- and double-scattering, computed from a predicted scatterer field acting as secondary sources, our method provides better illumination of the velocity model than conventional FWI. Using a new objective function, we optimized the source image and velocity model, including multiscattered energy, simultaneously. Because we conducted our method in the frequency domain with a complex source function including spatial and wavelet information, we mitigate the uncertainties of the source wavelet and source origin time. Inversion results from the Marmousi model indicate that by taking advantage of multiscattered energy and starting from a reasonably acceptable frequency (a single source at 3 Hz and multiple sources at 5 Hz), our method yields better inverted velocity models and source images compared with conventional FWI.

scholarly journals Two Wrongs Make a Right: Addressing Underreporting in Binary Data from Multiple Sources

2017 ◽  
Vol 25 (2) ◽  
pp. 223-240 ◽  
Author(s):  
Scott J. Cook ◽  
Betsabe Blas ◽  
Raymond J. Carroll ◽  
Samiran Sinha
Keyword(s):  
Binary Data ◽  
Science Research ◽  
Event Data ◽  
Multiple Sources ◽  
Secondary Sources ◽  
News Sources ◽  
The Social ◽  
Data Generating Process ◽  
Event Model ◽  
Conflict In Africa

Media-based event data—i.e., data comprised from reporting by media outlets—are widely used in political science research. However, events of interest (e.g., strikes, protests, conflict) are often underreported by these primary and secondary sources, producing incomplete data that risks inconsistency and bias in subsequent analysis. While general strategies exist to help ameliorate this bias, these methods do not make full use of the information often available to researchers. Specifically, much of the event data used in the social sciences is drawn from multiple, overlapping news sources (e.g., Agence France-Presse, Reuters). Therefore, we propose a novel maximum likelihood estimator that corrects for misclassification in data arising from multiple sources. In the most general formulation of our estimator, researchers can specify separate sets of predictors for the true-event model and each of the misclassification models characterizing whether a source fails to report on an event. As such, researchers are able to accurately test theories on both the causes of and reporting on an event of interest. Simulations evidence that our technique regularly outperforms current strategies that either neglect misclassification, the unique features of the data-generating process, or both. We also illustrate the utility of this method with a model of repression using the Social Conflict in Africa Database.

scholarly journals INTERACTIVE LEARNING IN THE COURSE OF INTERNAL MEDICINE: STEPS IN MAKING DIAGNOSIS

2020 ◽  
Vol 20 (2) ◽  
pp. 248-252
Author(s):  
T.G. Shekhovtseva ◽  
M.О. Dolinna
Keyword(s):  
Decision Making ◽  
Professional Training ◽  
Medical Decision Making ◽  
Interactive Learning ◽  
Diagnostic Errors ◽  
Educational Process ◽  
Medical Decision ◽  
Diagnostic Process ◽  
Clinical Thinking ◽  
Medical University

Current trends in the development of the Ukrainian education system provide a new approach to the organization of educational process. A doctor must know the algorithm of the diagnostic process and medical decision-making peculiarities underlying the making diagnosis. This requires constant improvement as the number of law cases has demonstrated that diagnostic errors are merely not due to physician’s insufficient medical qualification but often as a consequence of violation of the basic procedural laws. Studying the theory of medial diagnosis stimulates the development of clinical thinking. The purpose of this work was to systematize the main stages in making diagnosis and to outline the ways of their implementation through the interactive learning. The study involved the medical students of Zaporizhzhia State Medical University. The methodology included theoretical systematic analysis of scientific and methodological literature as well as own experience in applying interactive learning. The main motivating factor in the professional training organization should be focused on the professionally oriented use of material and fostering students’ own experience. Under these conditions, the importance of a semiotic approach to the diagnosis of diseases is increasing, i.e. the process of disease identification relies on the ability to catch and to recognise its signs. When making a diagnosis, the doctor has to rely on facts only. This is described as "clinical thinking." The interactive learning in the courses of various disciplines in the program of medical doctor training is being actively implemented at Zaporszhzhia State Medical University. It provides the opportunity for more pronounced pedagogical influence, which induces students to be more active in mastering the program, as well as to demonstrate creativity and research for solving various tasks in daily class practice. Deep understanding the theory of medical decision-making process and making diagnosis greatly contributes to clinical thinking.

scholarly journals Blind normalization of public high-throughput databases

2019 ◽  
Vol 5 ◽  
pp. e231
Author(s):  
Sebastian Ohse ◽  
Melanie Boerries ◽  
Hauke Busch
Keyword(s):  
High Throughput ◽  
Cell Biology ◽  
Large Scale ◽  
Missing Values ◽  
Ad Hoc ◽  
Confounding Factors ◽  
Noise Sources ◽  
Biological Signal ◽  
Public Data ◽  
Meta Analyses

The rise of high-throughput technologies in the domain of molecular and cell biology, as well as medicine, has generated an unprecedented amount of quantitative high-dimensional data. Public databases at present make a wealth of this data available, but appropriate normalization is critical for meaningful analyses integrating different experiments and technologies. Without such normalization, meta-analyses can be difficult to perform and the potential to address shortcomings in experimental designs, such as inadequate replicates or controls with public data, is limited. Because of a lack of quantitative standards and insufficient annotation, large scale normalization across entire databases is currently limited to approaches that demand ad hoc assumptions about noise sources and the biological signal. By leveraging detectable redundancies in public databases, such as related samples and features, we show that blind normalization without constraints on noise sources and the biological signal is possible. The inherent recovery of confounding factors is formulated in the theoretical framework of compressed sensing and employs efficient optimization on manifolds. As public databases increase in size and offer more detectable redundancies, the proposed approach is able to scale to more complex confounding factors. In addition, the approach accounts for missing values and can incorporate spike-in controls. Our work presents a systematic approach to the blind normalization of public high-throughput databases.

scholarly journals Speech-based Medical Decision Support in VR using a Deep Neural Network (Demonstration)

2017 ◽  
Author(s):  
Alexander Prange ◽  
Michael Barz ◽  
Daniel Sonntag
Keyword(s):  
Neural Network ◽  
Decision Support ◽  
Image Data ◽  
Medical Decision ◽  
Dialogue System ◽  
Medical Decision Support ◽  
Patient Database ◽  
History Of ◽  
Therapy Prediction ◽  
Radiology Image

We present a speech dialogue system that facilitates medical decision support for doctors in a virtual reality (VR) application. The therapy prediction is based on a recurrent neural network model that incorporates the examination history of patients. A central supervised patient database provides input to our predictive model and allows us, first, to add new examination reports by a pen-based mobile application on-the-fly, and second, to get therapy prediction results in real-time. This demo includes a visualisation of patient records, radiology image data, and the therapy prediction results in VR.

scholarly journals Alleviation or Politicization of Poverty in Africa? A Critique of Nigeria’s Social Investments Programs under Buhari-led Administration, 2015-2020

2021 ◽  
Vol 2 (2) ◽  
pp. 206-231
Author(s):  
Anthony Chinedu Ugwu ◽  
Dr. Al Chukwuma Okoli
Keyword(s):  
Ad Hoc ◽  
National Development ◽  
Social Investment ◽  
Wealth Creation ◽  
Poor Countries ◽  
Secondary Sources ◽  
The Social ◽  
Local Politicians ◽  
Balance Of Trade ◽  
Micro Level

The study interrogates the politics of poverty alleviation amidst the prevalence of poverty in Africa, focusing on Nigeria. Nigeria currently ranks among the poor countries in the world. While many studies have examined aspects of poverty mitigation within the national development frameworks, the politics underlying such endeavors have been under-explored. This study narrows this gap by investigating how politicians bastardize social investment programs through tokenish material 'hand-outs' designed to serve immediate political ends. The study is based on textual and contextual analysis of secondary sources, as complemented by corroborated anecdotes. Appropriating Marxian production theory, the study posits that the prevalence of poverty in Africa has been occasioned by macro and micro-level politics. At the macro-level, the balance of trade cum balance of payment asymmetries has reproduced conditions that perpetuate dependency and underdevelopment in the developing countries in general and Nigeria in particular. At the micro-level, local politicians trivialize social investments by exploiting the poverty situation of the populace for electoral gains through ad hoc material 'hand-outs.' This has weakened the social investment policy environment and alienated the citizenry in decision-making concerning wealth creation, distribution, and social investments priorities. The study recommends mainstreaming social investment governance into national development programing for sustainability.

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