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Medical AI & data Research group · Acıbadem Mehmet Ali Aydınlar University

ADALAB — Acıbadem Data Analytics Lab

Data science to improve the diagnostic and prognostic capacity of medical technologies.

  • 12members
  • 53projects
EEG electrode cap in front of a screen with brain-wave traces

What we work on

The Acıbadem Data Analytics Laboratory aims to use data science methods to improve the diagnostic and prognostic capacities of medical technologies and provides innovative data analytics solutions to improve clinical decision-making. It works through bioinformatics, biomechanics, cognitive neuroscience, artificial-intelligence-based approaches, optimisation of health processes and smart data-entry applications.

The laboratory was established in 2019 by Dr. Buğrahan Bayram, Dr. Sinem Burcu Erdoğan and Dr. Ata Akın. Early work used deep learning to classify melanomas; since then the team has taken on research questions in radiology, neuropsychiatry, neurorehabilitation, bioinformatics and sports medicine. Active topics are AI in radiology, rapid reporting via speech-to-text, AI for brain–machine interfaces, AI in neuropsychiatry and deep learning for clinical decision support.

While scientific projects come first, the laboratory also provides experimental and clinical measurement, validation, verification and prototyping services that companies in the health sector may need.

Lab website

Team 12

Principal investigator Dr. Sinem Burcu Erdoğan Faculty member, Biomedical Engineering; co-founder of the Acıbadem Data Analytics Lab Co-founded ADALAB in 2019 and leads its fNIRS brain-imaging and clinical decision-support work.

Projects & funders

Show all 53 projects

Selected outputs

  1. 2025

    ARGUNSAH H., ALTINTAŞ L., ŞAHİNER A. M. Eye-tracking insights into cognitive strategies, learning styles, and academic outcomes of Turkish medicine students. BMC MEDICAL EDUCATION, vol.25, no.1, 2025.

  2. 2024

    Aydınlar A., Mavi A., Kütükçü E., KIRIMLI E. E., ALİS D. C., AKIN A., et al. Awareness and level of digital literacy among students receiving health-based education. BMC Medical Education, vol.24, no.1, 2024.

  3. 2024

    Tanoren B. Calibration of scanning acoustic microscopy for the differentiation between unstable and stable atherosclerotic plaques by X-ray fluorescence imaging.. RADIATION PHYSICS AND CHEMISTRY, vol.224, pp.112058, 2024.

  4. 2024

    Eken A., Yüce M., Yükselen G., Erdoğan S. B. Explainable fNIRS-based pain decoding under pharmacological conditions via deep transfer learning approach.. Neurophotonics, vol.11, no.4, pp.45015, 2024.

  5. 2024

    AKIN A., Yorgancıgil E., Öztürk O. C., SÜTÇÜBAŞI B., KIRIMLI C. E., Elgün Kırımlı E. E., et al. Small world properties of schizophrenia and OCD patients derived from fNIRS based functional brain network connectivity metrics. SCIENTIFIC REPORTS, vol.14, no.1, 2024.

  6. 2024

    SÜTÇÜBAŞI B., BAYRAM A., Metin B., DEMİRALP T. Neural correlates of approach-avoidance behavior in healthy subjects: Effects of low-frequency repetitive transcranial magnetic stimulation (rTMS) over the right dorsolateral prefrontal cortex. INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, vol.203, 2024.

  7. 2024

    Argunsah H., Kaya E. Exploring the Contribution of Joint Angles and sEMG Signals on Joint Torque Prediction Accuracy using LSTM-Based Deep Learning Techniques. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, vol.28, no.13, pp.1-10, 2024.

  8. 2024

    Terzioglu S., Cogalmis K. N., Bulut A. Ad creative generation using reinforced generative adversarial network. ELECTRONIC COMMERCE RESEARCH, vol.24, no.3, pp.1491-1507, 2024.

  9. 2024

    Shirzadi S., Dadgostar M., Einalou Z., Erdoğan S. B., Akın A. Sex based differences in functional connectivity during a working memory task: an fNIRS study. FRONTIERS IN PSYCHOLOGY, vol.15, 2024.

  10. 2024

    TANOREN B., Dipcin B., Birdogan S., Unlu M. B., Ozdol C., Aghayev K. Examination of annulus fibrosus and nucleus pulposus in cervical and lumbar intervertebral disc herniation patients by scanning acoustic microscopy, scanning electron microscopy and energy dispersive spectroscopy. RSC ADVANCES, vol.14, no.4, pp.2603-2609, 2024.

From the group

Join us

We welcome students and researchers to our group. Write to Dr. Sinem Burcu Erdoğan to join, or bring a project idea and look at the instruments we can offer for collaboration.

Open to rotation students

Write to the group