Common publications | PARADISE

1. In project

Smaranda Belciug, RC Ivanescu, MS Serbanescu, F Ispas, R. Nagy, CM Comanescu, AM Istrate-Ofiteru, DG Iliescu

Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE) - protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection,

BMJ Open (accepted)

Smaranda Belciug

Learning deep neural networks’ architectures using differential evolution. Case study: medical imaging processing

Computers in Biology and Medicine, Q2, 105623

DOI: https://doi.org/10.1016/j.compbiomed.2022.105623

Dominic Iliescu, Smaranda Belciug (corresponding author), Renato Ivanescu, Roxana Dragusin, Monica Cara, Laurentiu Dira

Prediction of labor outcome pilot study: evaluation of primiparous women at term

American Journal of Obstetrics & Gynecology MFM, 4 (6), , 100711

DOI: https://doi.org/10.1016/j.ajogmf.2022.100711

Renato Ivanescu, Smaranda Belciug, Andrei Nascu, Mircea Serbanescu, Dominic Iliescu

Evolutionary computation paradigm to determine deep neural networks architectures

International Journal of Computers Communications & Control, 17, 5

DOI: https://doi.org/10.15837/ijccc.2022.5.4886

Smaranda Belciug, Dominic Iliescu

Pregnancy with Artificial Intelligence. A 9,5 months journey from preconception to birth

Springer Nature

DOI: https://doi.org/10.1007/978-3-031-18154-2

Smaranda Belciug, Iliescu, D.G.

Artificial Intelligence in Obstetrics.

In: Kwaśnicka, H., Jain, N., Markowska-Kaczmar, U., Lim, C.P., Jain, L.C. (eds) Advances in Smart Healthcare Paradigms and Applications. Intelligent Systems Reference Library, vol 244. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-031-37306-0_7

Smaranda Belciug, Nagy, R., Popa, S.D., Nascu, A.G., Iliescu, D.G.

Designing Deep Learning Architectures with Neuroevolution. Study Case: Fetal Morphology Scan

. In: Chen, YW., Tanaka, S., Howlett, R.J., Jain, L.C. (eds) Innovation in Medicine and Healthcare. KES InMed 2023. Smart Innovation, Systems and Technologies, vol 357. Springer, Singapore.

DOI: https://doi.org/10.1007/978-981-99-3311-2_23

Smaranda Belciug

Learning Paradigms for Neural Networks for Automated Medical Diagnosis

. In: Tsihrintzis, G.A., Virvou, M., Esposito, A., Jain, L.C. (eds) Advances in Assistive Technologies. Learning and Analytics in Intelligent Systems, vol 28. Springer-Nature, Cham.

DOI: https://doi.org/10.1007/978-3-030-87132-1_7

Nascu, A.G., Smaranda Belciug, Istrate-Ofiteru, AM., Iliescu, D.G.

Probabilistic Framework Based on Deep Learning for Differentiating Ultrasound Movie View Planes.

Holzinger, A., Kieseberg, P., Cabitza, F., Campagner, A., Tjoa, A.M., Weippl, E. (eds) Machine Learning and Knowledge Extraction. CD-MAKE 2023. Lecture Notes in Computer Science, vol 14065. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-031-40837-3_14

Smaranda Belciug, Renato Constantin Ivănescu, Andrei Nascu, Mircea Sebastian Serbănescu, Cristina Comănescu, Dominic Gabriel Iliescu

Knowledge-based statistical data analysis for deep learning and voting classifiers merger

Procedia Computer Science, Volume 225

DOI: https://doi.org/10.1016/j.procs.2023.10.417

2. Outside project

Istrate-Ofiţeru, A.-M.; Mogoantă, C.A.; Zorilă, G.-L.; Roşu, G.-C.; Drăguşin, R.C.; Berbecaru, E.-I.-A.; Zorilă, M.V.; Comănescu, C.M.; Mogoantă, S.-Ș.; Vaduva, C.-C.; Bratila, Iliescu nt. J. Mol. Sci. 2024, 25, 1789. https://doi.org/10.3390/ijms25031789

Clinical Characteristics and Local Histopathological Modulators of Endometriosis and Its Progression. I

J. Mol. Sci. 2024, 25, 1789

DOI: https://doi.org/10.3390/ijms25031789

Smaranda Belciug

Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research

Journal of Biomedical Informatics 102,

DOI: https://doi.org/10.1016/j.jbi.2019.103373

Smaranda Belciug, Florin Gorunescu

Learning a single-hidden layer feedforward neural network using rank correlation-based strategy with application to high dimenional gene expression and proteomic spectra datasets in cancer detection

Journal of Biomedical Informatics, 83, 159-166

DOI: 10.1016/j.jbi.2018.06.003

Laurentiu Mihai Dira, Stefania Tudorache, Panagiotis Antsaklis, George Daskalakis, Dagklis Themistoklis, Smaranda Belciug, Ruxandra Stoean, Marius Novac, Monica Laura Cara, Roxana Dragusin, Maria Florea, Ciprian Patru, Lucian Zorila, Rodica Nagy, Dan Ruican, Dominic Gabriel Iliescu,

Sonographic Evaluation of the Mechanism of Active Labor (SonoLabor Study): observational study protocol regarding the implementation of the sonopartogram

BMJ open, 11 (9), e047188,

DOI: http://dx.doi.org/10.1136/bmjopen-2020-047188

Smaranda Belciug, Adrian Sandita, Hariton Costin, Silviu Bejinariu, Pericle Matei

Competitive/Collaborative Statistical Learning Framework for Forecasting intraday stock market prices: a case study

Studies in Informatics and Control, 30 (2), 43-54

Smaranda Belciug, Silviu Bejinariu, Hariton Costin

An artificial immune system approach for a multi-compartment queuing model for improving medical resources and inpatient bed occupancy in pandemics

Advances in electrical and computer engineering, 20 (3), 23-30

Mircea Serbanescu, Nicolae Manea, Liliana Streba, Smaranda Belciug, Emil Plesea, Ionica Pirici, Raluca Bungardean, Mihail Plesa,

Automated gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks

Romanian Journal of Morphology and Embryology

DOI: doi: 10.47162/RJME.61.1.17

Dan Ruican, Ana-Maria Petrescu, Anda Ungureanu, Daniel Pirici, Marius Cristian Marinaș, Anca Maria Ofiteru, Mircea Serbanescu, Cristina Simionescu, Anne Marie Badiu, Gabriela-Camelia Roșu, Smaranda Belciug, Dominic Gabriel Iliescu

Virtual autopsy and confrimation of normal fetal heart anatomy in the first trimester using three-dimensional (3D) reconstruction of histological sections

Romanian Journal of Morphology and Embryology, 62 (1), 101-108

DOI: 10.47162/RJME.62.1.09

Iliescu, D.G., Smaranda Belciug, Gheonea, I.A

Simulation and Learning Curve of the Traditional and Sonographic Pelvimetry.

In: Cinnella, G., Beck, R., Malvasi, A. (eds) Practical Guide to Simulation in Delivery Room Emergencies. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-031-10067-3_16

Smaranda Belciug, R.C. Ivanescu

Non-parametric Rank Correlation Trained Single-Hidden Layer Feedforward Neural Networks for Medical Data,

Intelligent Methods Systems and Applications in Computing, Communication and Control, vol. 1435, 195-207, Springer-Nature,

Smaranda Belciug

Artificial Intelligence in Cancer - Diagnostic to tailored treatment

Elsevier, Academic Press

DOI: https://www.elsevier.com/books/artificial-intelligence-in-cancer/belciug/978-0-12-820201-2

Smaranda Belciug

An Introduction to Artificial Intelligence in Healthcare.

In: Lim, CP., Vaidya, A., Chen, YW., Jain, T., Jain, L.C. (eds) Artificial Intelligence and Machine Learning for Healthcare. Intelligent Systems Reference Library, vol 228. Springer-Nature, Cham

DOI: https://doi.org/10.1007/978-3-031-11154-9_1

Smaranda Belciug

Artificial Neural Networks for Precision Medicine in Cancer Detection

In: Virvou, M., Tsihrintzis, G.A., Jain, L.C. (eds) Advances in Selected Artificial Intelligence Areas. Learning and Analytics in Intelligent Systems, vol 24. Springer-Nature, Cham.

DOI: https://doi.org/10.1007/978-3-030-93052-3_11

Smaranda Belciug

Learning Paradigms for Neural Networks for Automated Medical Diagnosis

In: Tsihrintzis, G.A., Virvou, M., Esposito, A., Jain, L.C. (eds) Advances in Assistive Technologies. Learning and Analytics in Intelligent Systems, vol 28. Springer-Nature, Cham.

DOI: https://doi.org/10.1007/978-3-030-87132-1_7

Smaranda Belciug

A Statistical Analysis Handbook for Validating Artificial Intelligence Techniques Applied in Healthcare.

In: Lim, CP., Chen, YW., Vaidya, A., Mahorkar, C., Jain, L.C. (eds) Handbook of Artificial Intelligence in Healthcare. Intelligent Systems Reference Library, vol 212. Springer-Nature, Cham

DOI: https://doi.org/10.1007/978-3-030-83620-7_3

Smaranda Belciug, Florin Gorunescu

Intelligent Decision Support Systems—A Journey to Smarter Healthcare

Springer Nature

DOI: https://doi.org/10.1007/978-3-030-14354-1

Florin Gorunescu, Smaranda Belciug

Reference Module in Biomedical Sciences, Genetic Algorithms for Breast Cancer Diagnostics

Elsevier, Academic Press

DOI: https://doi.org/10.1016/B978-0-12-801238-3.00000-3

Smaranda Belciug

A Survival Analysis Guide in Oncology.

In: Lim, C.P., Vaidya, A., Chen, YW., Jain, V., Jain, L.C. (eds) Artificial Intelligence and Machine Learning for Healthcare. Intelligent Systems Reference Library, vol 229. Springer-Nature,

DOI: https://doi.org/10.1007/978-3-031-11170-9_2

Smaranda Belciug

Bed-Occupancy Management and Hospital Planning: A Handbook.

In: Shen, H., Zeng, Y., Li, L., Wang, X. (eds) Regionalized Management of Medicine. Translational Bioinformatics, vol 17. Springer-Nature,

DOI: https://doi.org/10.1007/978-981-16-7893-6_10

Toader, DO, Olaru RA, Iliescu Dominic Gabriel, Petrita R., Calagea FL, Petre, I

Clinical Performance and safety of vaginal ovules in the local treatment of nonspecific vaginitis: a national, multicentric clinical investigation

Clinical Therapeutics, 45, 9, 873-880

DOI: 10.1016/j.clinthera.2023.06.023

Ungureanu A, Marcu, A, Patru CL, Ruican D, Nagy, R., Stoean, R., Stoean, C, Iliescu Dominic Gabriel

Learning deep architectures for the interpretation of first-trimester fetal echocardiography (LIFE) – a study protocol for developing an automated intelligent decision support system for early fetal echocardiography,

BMC Pregnancy and Childbirth, 23, 1,

DOI: 10.1186/s12884-023-05825-w

Ruican, D, Petrescu, AM, Istrate-Ofiteru A, Rosu GC, Zorila GL, Dira LM, Nagy R, Mogoanta, L, Pirici, D, Iliescu Dominic Gabriel,

Confirmation of Heart malformations in fetuses in the first trimester using three dimensional histologic autopsy

141, 6, 1209-1218

DOI: 10.1097/AOG. 0000000000005169

Țieranu, M.-L.; Dragoescu, N.A.; Zorilă, G.-L.; Istrate-Ofițeru, A.-M.; Rămescu, C.; Berbecaru, E.-I.-A.; Drăguşin, R.C.; Nagy, R.D.; Căpitănescu, R.G.; Iliescu Dominic Gabriel

Addressing Chronic Gynecological Diseases in the SARS-CoV-2 Pandemic

Medicina, 59, 802.

DOI: https://doi.org/10.3390/medicina59040802

Ungureanu, D.R.; Drăgușin, R.C.; Căpitănescu, R.G.; Zorilă, L.; Ofițeru, A.M.I.; Marinaș, C.; Pătru, C.L.; Comănescu, A.C.; Comănescu, M.C.; Sîrbu, O.C, Vrabie, MS, Dijmarescu, LA, Streata, I, Burada, F, Ioana, M, Dragoescu, AN, Iliescu Dominic Gabriel;

First Trimester Ultrasound Detection of Fetal Central Nervous System Anomalies

Brain Sci. 2023, 13, 118.

DOI: https://doi.org/10.3390/brainsci13010118

Zorila, GL, Capitanescu RG, Dragusin, RC, Istrate-Ofiteru, AM, Bernad, E, Dobie, M, Bernad, S, Craina, M, Ceausu, I, Marinas, MC, Comanescu MC, Zorila MV, Drocas, I, Berbecaru, EIA, Iliescu Dominic Gabriel

Uterine Perforation as a Complication of the Intrauterine Procedures Causing Omentum Incarceration: A Review

Diagnostics 2023, 13, 331.

DOI: https://doi.org/10.3390/diagnostics13020331

Dhombres, F, Morgan, P, Chaudhari, BP, Filges, I, Sparks, TN, Lapunzina, P, Roscioli, T, Agarwal, U, Aggarwal, S, Beneteau, C, Cacheiro, P, Carmody, LC, Corllardeau Franchon, S, el Ghosh, M, Giordanu, JL, Glad, R, Grinfelde, I, Iliescu Dominic Gabriel, Ladewig, MS, Munos, Torres, MC, Pollanzon, M, Radio, FC, Rodo, C, Silva, RG, Smedley, D,

Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology

American J Med Genetics Part C – Seminars in medical genetics, 190, 2, 231-242,

DOI: 10.1002/ajmg.c31989

Dîră LM, Cara M-L, Drăgușin RC, Nagy RD, Iliescu Dominic Gabriel.

The Value of Fetal Head Station as a Delivery Mode Predictor in Primiparous Women at Term before the Onset of Labor.

Journal of Clinical Medicine. 2022; 11(12):3274.

DOI: https://doi.org/10.3390/jcm11123274

Istrate-Ofiţeru A-M, Berbecaru E-I-A, Zorilă G-L, Roşu G-C, Dîră LM, Comănescu CM, Drăguşin RC, Ruican D, Nagy RD, Iliescu Dominic Gabriel, et al.

Specific Local Predictors That Reflect the Tropism of Endometriosis—A Multiple Immunohistochemistry Technique

International Journal of Molecular Sciences.2022; 23(10):5614.

DOI: https://doi.org/10.3390/ijms23105614

Nagy RD, Ruican D, Zorilă G-L, Istrate-Ofiţeru A-M, Badiu AM, Iliescu DG.

Feasibility of Fetal Portal Venous System Ultrasound Assessment at the FT Anomaly Scan

Diagnostics. 2022; 12(2):361.

DOI: https://doi.org/10.3390/diagnostics12020361

Cara ML, Streata I, Buga AM, Iliescu Dominic Gabriel

Developmental Brain Asymmetry. The Good and the Bad Sides.

Symmetry. 2022; 14(1):128.

DOI: https://doi.org/10.3390/sym14010128

Istrate-Ofițeru A-M, Berbecaru E-I-A, Ruican D, Nagy RD, Rămescu C, Roșu G-C, Iovan L, Dîră LM, Zorilă G-L, Țieranu M-L, Iliescu Dominic Gabriel.

The Influence of SARS-CoV-2 Pandemic in the Diagnosis and Treatment of Cervical Dysplasia.

Medicina. 2021; 57(10):1101.

DOI: https://doi.org/10.3390/medicina57101101

Miescu, M, Novac, M, Ruican, D, Nagy, RD, Iliescu, DG

Twelve weeks of reversed umbilical flow in the fetal growth restriction case associated with severe periconceptional maternal anemia,

, J Ultrasound in Medicine, 39, 9, 1873-1875

DOI: 10.1002/jum.15274

Cherciu Harbiyeli IF, Burtea DE, Serbanescu M-S, Nicolau CD, Saftoiu A.

Implementation of a Customized Safety Checklist in Gastrointestinal Endoscopy and the Importance of Team Time Out—A Dual-Center Pilot Study

Medicina. 2023; 59(6):1160.

DOI: https://doi.org/10.3390/medicina59061160

Savu E, Vasile L, Serbanescu M-S, Alexandru DO, Gheonea IA, Pirici D, Paitici S, Mogoanta SS.

Clinicopathological Analysis of Complicated Colorectal Cancer: A Five-Year Retrospective Study from a Single Surgery Unit

Diagnostics. 2023; 13(12):2016.

DOI: https://doi.org/10.3390/diagnostics13122016

Teică RV, Șerbănescu M-S, Florescu LM, Gheonea IA

Tumor Area Highlighting Using T2WI, ADC Map, and DWI Sequence Fusion on bpMRI Images for Better Prostate Cancer

, Life.2023;13(4):910.

DOI: https://doi.org/10.3390/life13040910

Mămuleanu M, Urhuț CM, Săndulescu LD, Kamal C, Pătrașcu A-M, Ionescu AG, Șerbănescu M-S, Streba CT

Deep Learning Algorithms in the Automatic Segmentation of Liver Lesions in Ultrasound Investigations

. Life. 2022; 12(11):1877.

DOI: https://doi.org/10.3390/life12111877

Harbiyeli IFC, Burtea DE, Ivan ET, Streață I, Nicoli ER, Uscatu D, Șerbănescu M-S, Ioana M, Vilmann P, Săftoiu A.

Assessing Putative Markers of Colorectal Cancer Stem Cells: From Colonoscopy to Gene Expression Profiling

Diagnostics. 2022; 12(10):2280

DOI: https://doi.org/10.3390/diagnostics12102280

Florescu LM, Streba CT, Şerbănescu M-S, Mămuleanu M, Florescu DN, Teică RV, Nica RE, Gheonea IA.

Federated Learning Approach with Pre-Trained Deep Learning Models for COVID-19 Detection from Unsegmented CT images

. Life. 2022; 12(7):958.

DOI: https://doi.org/10.3390/life12070958

Oancea C-N, Statie R-C, Gheonea D-I, Ciurea T, Șerbănescu M-S, Streba C-T.

IBD Monitor: Romanian National Mobile Application for Inflammatory Bowel Disease Personalized Treatment and Monitoring

Diagnostics. 2022; 12(6):1345.

DOI: https://doi.org/10.3390/diagnostics12061345

Fraggetta F, L’Imperio V, Ameisen D, Carvalho R, Leh S, Kiehl T-R, Serbanescu M, Racoceanu D, Della Mea V, Polonia A, et al.

Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP).

Diagnostics. 2021; 11(11):2167

DOI: https://doi.org/10.3390/diagnostics11112167

Nica, RE., Șerbănescu, MS., Florescu, LM. et al

Deep Learning: a Promising Method for Histological Class Prediction of Breast Tumors in Mammography

J Digit Imaging 34, 1190–1198

DOI: https://doi.org/10.1007/s10278-021-00508-4

3. Citations Q1 from 2019 to present

F Gorunescu, M Gorunescu, E El-Darzi, S Gorunescu, K Revett, A cancer diagnosis system based on rough sets and probabilistic neural networks, Proceedings of the first european conference on health care modelling and computation, University of Medicine and Pharmacy of Craiova, 149-159, 2005

Jones OT, Calanzani N, Saji S, Duffy SW, Emery J, Hamilton W, Singh H, de Wit NJ, Walter FM Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review

J Med Internet Res 2021;23(3):e23483

Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Marius Ene, Smaranda Gorunescu, Statistical comparison of a probabilistic neural network approach in hepatic cancer diagnosis, EUROCON 2005-The International Conference on Computer as a Tool, 237-240, 2005

Jones OT, Calanzani N, Saji S, Duffy SW, Emery J, Hamilton W, Singh H, de Wit NJ, Walter FM Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review

J Med Internet Res 2021;23(3):e23483

Smaranda Belciug, Monica Lupsor, A multi-layer based procedure for detecting liver fibrosis, Annals of the University of Craiova-Mathematics and Computer Science, 36 (1), 64-70, 2009

Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, , Expert Systems with Applications Volume 170, 15 May 2021, 114538

F Gorunescu, S Belciug, M Gorunescu, M Lupsor, R Badea, H Stefanescu, Smaranda Belciug Radial basis function network-based diagnosis for liver fibrosis estimation, Proc. 2nd Intl. Conf. on e-Health and Bioengineering, 17-18m 2009

Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, Expert Systems with Applications Volume 170, 15 May 2021, 114538

Smaranda Belciug, A Salem, F Gorunescu, Marina Gorunescu, Clustering-based approach for detecting breast cancer recurrence.: IEEE, 2010

Jones OT, Calanzani N, Saji S, Duffy SW, Emery J, Hamilton W, Singh H, de Wit NJ, Walter FM Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review J Med Internet Res 2021;23(3):e23483

Florin Gorunescu, Marina Gorunescu, Adrian Saftoiu, Peter Vilmann, Smaranda Belciug, Competitive/collaborative neural computing system for medical diagnosis in pancreatic cancer detection, Expert Systems, 28, 33-48, 2011

C Tang, J Ji, Y Tang, S Gao, Z Tang, Y Todo, A novel machine learning technique for computer-aided diagnosis, Engineering Applications of Artificial Intelligence Volume 92, June 2020, 103627

S Belciug, DG Iliescu, Deep learning and Gaussian Mixture Modelling clustering mix. A new approach for fetal morphology view plane differentiation, Journal of Biomedical Informatics Volume 143, July 2023, 104402

Florin Gorunescu, Smaranda Belciug, Marina Gorunescu, Radu Badea, Intelligent decision-making for liver fibrosis stadialization based on tandem feature selection and evolutionary-driven neural network, Expert Systems with Applications, 39, 17, 12824-12832, 2012

Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, Expert Systems with Applications Volume 170, 15 May 2021, 114538

Florin Gorunescu, Smaranda Belciug, Evolutionary strategy to develop learning-based decision systems. Application to breast cancer and liver fibrosis stadialization, Journal of biomedical informatics,49, 112-118, 2014

O Ben-Assuli, A Jacobi, O Goldman, et al, Stratifying individuals into non-alcoholic fatty liver disease risk levels using time series machine learning models Journal of Biomedical Informatics Volume 126, February 2022, 103986

S Belciug, DG Iliescu, Deep learning and Gaussian Mixture Modelling clustering mix. A new approach for fetal morphology view plane differentiation, Journal of Biomedical Informatics Volume 143, July 2023, 104402

Smaranda Belciug, Florin Gorunescu, Error-correction learning for artificial neural networks using the Bayesian paradigm. Application to automated medical diagnosis, Journal of Biomedical Informatics Volume 52 Pages 329-337, 2014

Smaranda Belciug, Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research, Journal of Biomedical Informatics Volume 102, February 2020, 103373

Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, Expert Systems with Applications Volume 170, 15 May 2021, 114538

Smaranda Belciug, Florin Gorunescu, Improving hospital bed occupancy and resource utilization through queuing modeling and evolutionary computation, Journal Journal of biomedical informatics Volume 53 Pages 261-269, 2015

L He, SC Madathil, A Oberoi, G Servis, et al., A systematic review of research design and modeling techniques in inpatient bed management, Computers & Industrial Engineering Volume 127, January 2019, Pages 451-466

Navid Izady , Israa Mohamed, A Clustered Overflow Configuration of Inpatient Beds in Hospitals, Manufacturing & Service operations management, 23, 1, https://doi.org/10.1287/msom.2019.0820

Sharma N, Schwendimann R, Endrich O, Ausserhofer D, Simon M Variation of Daily Care Demand in Swiss General Hospitals: Longitudinal Study on Capacity Utilization, Patient Turnover and Clinical Complexity Levels J Med Internet Res 2021;23(8):e27163 doi: 10.2196/27163

X Gong, X Wang, L Zhou, N Geng, Managing hospital inpatient beds under clustered overflow configuration, Computers & Operations Research Volume 148, December 2022, 106021

X Chen, Y Dong, M Wu , et al,A long-term forecasting and simulation model for strategic planning of hospital bed capacity, Risk analysis, Volume43, Issue6 June 2023Pages 1187-1211

Smaranda Belciug, Florin Gorunescu, A hybrid genetic algorithm-queuing multi-compartment model for optimizing inpatient bed occupancy and associated costs, Artificial intelligence in medicine Volume 68 Pages 59-69, 2016

Lu He, et al., A systematic review of research design and modeling techniques in inpatient bed management, Computers & Industrial Engineering Volume 127, January 2019, Pages 451-466

Li, T., et al., A systematic review and comprehensive analysis of building occupancy prediction, Renewable and Sustainable Energy Reviews Volume 193, April 2024, 114284

Patel, B., et al., Operations Research Techniques and Its’ Application in Healthcare Service Delivery Decision Making: A Review of Evolution, Journal of Management, 6(2), 2019, pp. 168-176, 2020

F Gorunescu, S Belciug, Boosting backpropagation algorithm by stimulus-sampling: Application in computer-aided medical diagnosis, Journal of biomedical informatics 63, 74-81, 2016

Smaranda Belciug, Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research, Journal of Biomedical Informatics Volume 102, February 2020, 103373

F Gorunescu, S Belciug, Boosting backpropagation algorithm by stimulus-sampling: Application in computer-aided medical diagnosis, Journal of biomedical informatics 63, 74-81, 2016

Jones OT, Calanzani N, Saji S, Duffy SW, Emery J, Hamilton W, Singh H, de Wit NJ, Walter FM Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review J Med Internet Res 2021;23(3):e23483 doi: 10.2196/23483

F Gorunescu, S Belciug, Boosting backpropagation algorithm by stimulus-sampling: Application in computer-aided medical diagnosis, Journal of biomedical informatics 63, 74-81, 2016

Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, Expert Systems with Applications Volume 170, 15 May 2021, 114538

F Gorunescu, S Belciug, Boosting backpropagation algorithm by stimulus-sampling: Application in computer-aided medical diagnosis, Journal of biomedical informatics 63, 74-81, 2016

Sinha, B.B., Ahsan, M. & Dhanalakshmi, R. LightGBM empowered by whale optimization for thyroid disease detection. Int. j. inf. tecnol. 15, 2053–2062 (2023). https://doi.org/10.1007/s41870-023-01261-3

Zhongheng Zhang, Victor Trevino, Sayed Shahabuddin Hoseini, Smaranda Belciug, Arumugam Manivanna Boopathi, Ping Zhang, Florin Gorunescu, Velappan Subha, Songshi Dai, Variable selection in logistic regression model with genetic algorithm, Annals of translational medicine Volume 6 Issue 3, 2018

Jayakumar Kaliappan, et al., Front. Public Health, 14 September 2021, Performance evaluation of regression models for the prediction of the COVID-19 reproduction rate Sec. Digital Public Health Volume 9 - 2021 | https://doi.org/10.3389/fpubh.2021.729795

Dongjie Chen, et al., Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients, Int J Biol Sci. 2022; 18(1): 360–373.

R Norat, AS Wu, X Liu , Genetic algorithms with self-adaptation for predictive classification of Medicare standardized payments for physical therapists, Expert Systems with Applications Volume 218, 15 May 2023, 119529

S Belciug, F Gorunescu, Learning a single-hidden layer feedforward neural network using a rank correlation-based strategy with application to high dimensional gene expression and proteomic spectra datasets in cancer detection Author links open overlay panel, Journal of Biomedical Informatics Volume 83, July 2018, Pages 159-166

Lin, X., A new data analysis method based on feature linear combination, Journal of Biomedical Informatics Volume 94, June 2019, 103173

Smaranda Belciug, Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research, Journal of Biomedical Informatics Volume 102, February 2020, 103373

Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, Expert Systems with Applications Volume 170, 15 May 2021, 114538

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S Belciug, F Gorunescu, S Belciug, F Gorunescu - Intelligent Decision Support Systems, Era of intelligent systems in healthcare, 1-55, Springer, 2020

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Smaranda Belciug, Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research, Journal of Biomedical Informatics Volume 102, February 2020, 103373

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Smaranda Belciug, Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data, Expert Systems with Applications Volume 170, 15 May 2021, 114538

S Belciug, Artificial Intelligence in Cancer: diagnostic to tailored treatment, Elsevier, 2020

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