PUBLICATIONS:
“Using Deep Convolutional Neural Network to Create a DCNN Model for Brain Tumor Detection” Eur. Chem. Bull. 2023,12(Special Issue 7), 4979-4989, doi: 10.48047/ecb/2023.12.si7.430
“MRI Image Segmentation with HDBrainExtraction Extension in 3D Slicer” Eur. Chem. Bull. 2023,12(Special Issue 7), 4973-4978, doi: 10.48047/ecb/2023.12.si7.429
“An Overview Of Protocol For Quality Control Tests For Diagnostic Radiology Applied By Albmedtech” Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), ISSN: 1671-5497. E-Publication: Online Open Access, Vol: 42 Issue: 11-2023, DOI: 10.5281/zenodo.10081328, Scopus Journal, SJR 0.218.
“Higher Education Study Programs Orientation on the Applications of Artificial Intelligence”, Migration Letters, 20(S8), 377–383. Retrieved from https://migrationletters.com/index.php/ml/article/view/4615, Scopus Journal, SJR 0.468
“Integration of DCNN Model for Brain Tumor Detection with PPIR Simulator” International Journal of Intelligent Systems and Applications in Engineering, ISSN: 2147-6799. Accepted for publication Special Issue, December 2023, Scopus Journal https://www.scopus.com/sourceid/21101021990, SJR 0.234.
“Artificial Intelligence in Medical Image Processing” International Journal of Intelligent Systems and Applications in Engineering, ISSN: 2147-6799. Accepted for publication Special Issue, December 2023, Scopus Journal https://www.scopus.com/sourceid/21101021990, SJR 0.234.
CONFERENCES:
- Dafina Xhako, Niko Hyka, Kita Sallabanda, Partizan Malkaj, “MRI Image Segmentation with HDBrainExtraction Extension in 3D Slicer” in International Conference on Artificial Intelligence in Medical Applications (ICAIMA - 23), Hamburg, Germany on 8th Jun - 9th Jun'2023. Proceedings in Eur. Chem. Bull. 2023,12(Special Issue 7), 4973-4978, doi: 10.48047/ecb/2023.12.si7.429
- Niko Hyka, Dafina Xhako, Kita Sallabanda, Partizan Malkaj, “Using Deep Convolutional Neural Network to Create a DCNN Model for Brain Tumor Detection” in International Conference on Artificial Intelligence in Medical Applications (ICAIMA - 23), Hamburg, Germany on 8th Jun - 9th Jun'2023. Proceedings in Eur. Chem. Bull. 2023,12(Special Issue 7), 4979-4989, doi: 10.48047/ecb/2023.12.si7.430
- Niko Hyka, Dafina Xhako, Partizan Malkaj, “Evaluation of Radiology Devices Quality Compared To COCIR Standards And The Problems Observed During The Facing Of The Covid 19 Pandemic”, International Conference on Radiation Applications (RAP 2023), Attica, Greece, from May 29 to June 2, 2023, proceedings in Applied Radiation and Isotopes in press…
- Niko Hyka, Dafina Xhako, Gerta Halilaj, “An overview on medical imaging system in Albania during the COVID-19 pandemic”, BPU11 Congres (The 11th International Conference of the Balkan Physical Union), 28 August – 1 September 2022, The Book of Abstracts, Editors: Antun Balaž, Goran Djordjević, Jugoslav Karamarković, Nenad Lazarević Technical Editor: Milan Milošević Cover Design: Elena Denda Printed by: Planeta Print, Belgrade, ISBN: 978-86-7025-950-8.
- Dafina Xhako, Niko Hyka, Kita Sallabanda, Rudina Zeqirllari, Partizan Malkaj and Joan Jani, “Development of auto-segmentation models for medical images processing” the Second Conference organized by the National Institute of Physics (NIP) 28-29 April, 2023, Academy of Sciences of Albania, Book of Abstracts, ISBN 9789928173935.
- Dafina Xhako, Niko Hyka, Suela Hoxha, Uada Bitri, Partizan Malkaj, “Evaluation of quality radiologic devices using RTI evaluation method and comparing the results with international standards” "NANOBALKAN2023 International Conference", Tirana, Albania, October 16-20, 2023, Book of Abstracts.
- Elda Spahiu, Suela Hoxhaj, Dafina Xhako, Niko Hyka, “The use of AI algorithms for identifying key parameters in medical images” The International Congress on Scientific Research Conference, 28-29 November 2023, ISKAD Institute, Turkey.
- Suela Hoxhaj, Elda Spahiu, Dafina Xhako, Niko Hyka, “The impact of radiological examinations during the COVID 19 in the number of tumors in the following years in Albania” The International Congress on Scientific Research Conference, 28-29 November 2023, ISKAD Institute, Turkey.
Applications of AI in medical imaging and in radiotherapy
Artificial intelligence (AI) is a disruptive technology that involves the use of computerised algorithms to dissect complicated data. Among the most promising clinical applications of AI is diagnostic imaging, and mounting attention is being directed at establishing and fine-tuning its performance to facilitate detection and quantification of a wide array of clinical conditions. Investigations leveraging computer-aided diagnostics have shown excellent accuracy, sensitivity, and specificity for the detection of small radiographic abnormalities, with the potential to improve public health. However, outcome assessment in AI imaging studies is commonly defined by lesion detection while ignoring the type and biological aggressiveness of a lesion, which might create a skewed representation of AI's performance. Moreover, the use of non-patient-focused radiographic and pathological endpoints might enhance the estimated sensitivity at the expense of increasing false positives and possible overdiagnosis as a result of identifying minor changes that might reflect subclinical or indolent disease. We argue for refinement of AI imaging studies via consistent selection of clinically meaningful endpoints such as survival, symptoms, and need for treatmen
