Theses

Computational Medicine Research Group specializes in artificial intelligence, machine learning, application of mathematical and computational models to routine clinical medicine.

Ph.D Theses in Progress

Algorithmic Learning Of Clinically Acceptable Levels Of Laboratory Test Results From Electronic Medical Records: Personalized Reference Intervals, Oktay YILDIRIM

Acceptable laboratory test intervals to be learned from hospital data using artificial intelligence algorithms, to provide a personalized reference interval with learned intervals.

Capturing Data From Clinical Examination By Motion Tracking And Recognition, Ramiz YILMAZER

The visual and audio recordings of the interaction of the physician with the patient during the clinical examination are understood by artificial intelligence algorithms and the data captured is stored as part of patient's electronic health records.

Machine Learning Models For Identifying Cause Effect Relationship In Medical Treatment Data, Mohammed Abebe YIMER

The machine-learning model involves evaluating and learning the effects of a treatment applied to a patient. Using electronic health records of patients, the model learns the cause effect relationships between the treatment and the results of the treatment and tries to bring these cause-effect relations to the attention of the physician using machine-learning algorithms.

MSc Theses in Progress

System For Planning, Staging And Ordering Of Diagnostic Laboratory Tests, Eminullah YAŞAR

Tübitak Project(2017 Ağustos - 2019 Şubat), Patent No:PT2016-01677

In this project, a system is implemented that can execute and coordinate staged ordering and execution of diagnostic laboratory tests.

Application Of Machine Learning Algorithms To Taking Of Anamnesis, Mehdi MOHAMMADNEJADIAN

A system that allows narration to be taken from the patient using artificial intelligence is being implemented. Patient story combined with patient's electronic healt records is used to generate several hypotheses relevant to patient's clinical condition.

Experiementing With Some Data Mining Techniques To Establish Pediatric Reference Intervals For Clinical Laboratory Tests, Deniz ERASLAN

An environment for determination of reference intervals for laboratory tests for pediatric patients, using data mining techniques on electronic health records.

Application Of Probabilistic Programming To Medicine, Adili AIERPATI

Application of probabilistic learning techniques in health problems.

BSc Theses In Progress

Identification And Monitoring Of Internal Quality Control Nonconfirmities In Medical Laboratories, Necati BİLGİN

Identification and monitoring of internal quality control nonconformities in medical laboratories.

Completed Ph.D Theses

Organization And Processing Of Personal Genetic Data For Clinical Use, Onur ÇAKIRGÖZ

In this study, two different databases were developed for the organization of variation-based personal genetic data. The first from these databases is the relational database, and the second is the no-sql database. In both databases, the variation data of 2504 individuals, which were published by 1000 Genomes Projects, were stored. To store this data, the spaces needed by the databases were calculated and compared. In addition, some queries that are frequently used by clinical applications were run and the response times of the databases were calculated. In this study, three new methods for three different clinical applications were also developed and the integration of databases with these methods was provided. The first method classifies individuals as disease-based, finds individuals who are genetically most similar to a person and calculates the disease risks of the individuals. The second method dynamically detects variations that may be associated with any disease or treat. The last method identifies protected regions using variation-based personal genetic data.

Theses Done In Collaboration With Medical Faculty

Artificial Neural Network Approach In Laboratory Test Reporting, Ferhat DEMİRCİ

In the field of laboratory medicine, minimizing errors and establishing standardization is only possible by predefined processes. The aim of this study was to build an experimental decision algorithm model open to improvement that would efficiently and rapidly evaluate the results of biochemical tests with critical values by evaluating multiple factors concurrently.

Completed MSc Theses

Development Of Computational Methods For Creative Visual Design, Ramiz YILMAZER

Preparing visual designs by artificial intelligence.

Machine Learning Models For Autoverification Of Medical Laboratory Test Results, Velid Ali

Automatic confirmation of the results of medical laboratory tests using artificial intelligence.

Publications

Artificial Neural Network Approach In Laboratory Test Reporting: Learning Algorithms

F Demirci, P Akan, T Kume, AR Sisman, Z Erbayraktar, S Sevinc American journal of clinical pathology 146 (2), 227-237. Go to the Article

An Efficient Method For Storing Human Genome Variations.

Çakırgöz, O., & Sevinç, S. (2015). Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science (EECSS 2015), 314, 1–8.Go to the Article

A Dynamic Method For The Determination Of The Variations Which May Be Associated With Any Disease Or Trait.

Çakırgöz, O., & Sevinç, S. (2016). Proceedings of the International Conference on Computer Science and Engineering (UBMK 2016), 16, 89–99.

Genetic-based Classification Approach And A Common Format For Relative Risk Models.

Çakırgöz, O., & Sevinç, S. (2016). Proceedings of the International Conference on Computer Science and Engineering (UBMK 2016), 24, 143-148.

Object-oriented Design For Processing Of Variation-based Personal Genetic Data.

Çakırgöz, O., & Sevinç, S. (2016). Proceedings of the International Conference on Computer Science and Engineering (UBMK 2016), 37, 214-222.

A Novel Tree Design To Determine Conserved Regions.

Çakırgöz, O., & Sevinç, S. (2016). International Conference on Advanced Technology & Sciences ICAT'Rome, 23–31.

OUR PROJECT

Projects as Computational Medicine Group

R&D PRODUCTS

As a result of our studies, we obtained 3 patent applications, academic publications, industrial projects, research projects and we continue to work.

TÜBİTAK

Lab Standards Plus DDX: System for the Planning and Progressing of Medical Investigations for Diagnosis (2017 August - 2019 August)

Lab Standards Plus PQ:Predictive Quality Control System in Medical Laboratories (2017 November – 2018 November)

KOSGEB

Lab Standards Plus: Advanced Technology Based Medical Laboratory Quality and Data Management System (2015 March-2017 March)

Lab Standards Plus: Predictive Quality Management System (2017 December-2019 June)

PATENTS

Distributed, real-time, message-based system that enables active planning, monitoring, clinical evaluation of medical laboratory tests and minimization of process errors (PT2016-00486)

The system for the planning and phasing of medical examinations for diagnosis (PT2016-01677)

System that provides blood collection in one station (2017/09583)

TEAM

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Prof. Dr. Süleyman SEVİNÇ
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Prof. Dr. Alİ Rıza ŞİŞMAN
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Dr.Onur ÇAKIRGÖZ
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Oktay YILDIRIM
Computer Engineer(PhDc)
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Ramİz YILMAZER
Computer Engineer(PhDc)
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Mohammed ABEBE
Computer Engineer(PhDc)
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Eminullah YAŞAR
Computer Engineer(MSc)
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Mehdİ Nejadİan
Computer Engineer(MSc)
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Denİz Eraslan
Computer Engineer(MSc)
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Burak KÖSE
Computer Engineer(MSc)
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Necatİ Bİlgİn
Computer Engineer(Undergraduate)
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Aykut ÖzgÜn
Computer Engineer(Undergraduate)
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Fethan Us
Computer Engineer(Undergraduate)
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Mehmet Sefa AYIZ
Computer Engineer(Undergraduate)
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Alİ AKARSU
Computer Engineer(Undergraduate)

PROGRAMMES

Computational Medicine offers BSc, MSc, Ph.D education.

COOPERATIONS

ACTIVITIES

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2. International Participated Health 4.0, Health Innovation Congress

Prof. Dr. Semih Başkan 4-7 October 2017 Health

Dear Colleagues, Okan University Faculty of Medicine With the international participation of DoktorClub on 04-07 October 2018 ..

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New Approaches Based on Artificial Intelligence in Medicine

Prof. Dr. Süleyman Sevinç Prof. Dr. Ali Rıza Şişman 29 November 2017 Informatic-Health

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New Approaches Based on Artificial Intelligence in Medicine

HSU Ttrh 6 December 2017 Informatic-Health

The Symposium on "New Approaches Based on Artificial Intelligence in Tıpta" was held in Health Sciences University Tepecik Training and Research Hospital. Researchers interested in "Artificial Intelligence", scientists, health workers and software ...

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PRESENTATIONS

PRESS

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Artificial intelligence in Izmir reduced patient waiting time

Technology

İzmir Tepecik Education and Research Hospital has 900 to 1000 patients daily

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'Artificial Intelligence' system for hospitals

Technology

Turkish scientists will avoid unnecessary testing of the disease, quickly evaluate the test results...

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Artificial intelligence system from Turkish scientists for hospitals

Technology

Turkish scientists will avoid unnecessary testing of the disease, quickly evaluate the test results...

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'Artificial Intelligence' system for hospitals

Technology

"Artificial intelligence" system for hospitals - Turkish scientists will be able to avoid unnecessary testing of sickness, quickly assessing test results...

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CONTACT US

Send

ADDRESS

Mithatpaşa Street No: 56/20 Dokuz Eylül University Technology Olive Building Office No: 112 Balçova-İzmir

CALL US

(0232) 277 55 59

EMAIL

info@labenko.com

WORKING HOURS

7/24