Dr. Muhammad Salman Haleem

Muhammad Salman Haleem

Lecturer (Assistant Professor) in Computer Science

Electronic Engineering and Computer Science
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Research

Artificial Intelligence, Biomedical Signal and Image Processing, Digital Twin

Cancer Models, Cardiovascular Models

Interests

Fundamental AI design and development of mathematical foundations of AI to address personalized risk assessment models. It require time series data acquisition, processing and modelling from multiple sources such as modern assistive technologies, health questionnaires, electronic health records etc. Pivotal for modern chronic disease management

Publications

Publications of specific relevance to Predictive in vitro Models

2024

Rotbei S, Tseng WH, Merino-Barbancho B, Haleem MS, Montesinos L, Pecchia L, Fico G and Botta A (2024). Evaluating impact of movement on diabetes via artificial intelligence and smart devices systematic literature review. Elsevier  Expert Systems With Applications  vol. 257,  
Ellison M, Haleem MS and Bannister J (2024). Qualifying the volumes of Mental Ill Health incident dealt with by Greater Manchester Police (GMP). 
Haleem MS, Cisuelo O, Andellini M, Castaldo R, Angelini M, Ritrovato M, Schiaffini R, Franzese M and Pecchia L (2024). A Self-Attention Deep Neural Network Regressor for real time blood glucose estimation in paediatric population using physiological signals. Elsevier  Biomedical Signal Processing and Control  vol. 92,  
Andellini M, Castaldo R, Cisuelo O, Franzese M, Haleem MS, Ritrovato M, Pecchia L and Schiaffini R (2024). Are the variations in ECG morphology associated to different blood glucose levels? implications for non-invasive glucose monitoring for T1D paediatric patients. Elsevier  Diabetes Research and Clinical Practice  vol. 212,  

2023

Haleem MS (2023). Advances in Artificial Intelligence, Machine Learning and Deep Learning Applications. Mdpi  Electronics  vol. 12, (18) 3780-3780.  
Maccaro A, Pagliara SM, Zarro M, Piaggio D, Abdulsalami F, Su W, Haleem MS and Pecchia L (2023). Ethics and biomedical engineering for well-being: a cocreation study of remote services for monitoring and support. Nature Research  Scientific Reports  vol. 13, (1) 14322-14322.  
Haleem MS, Ekuban A, Antonini A, Pagliara S, Pecchia L and Allocca C (2023). Deep-Learning-Driven Techniques for Real-Time Multimodal Health and Physical Data Synthesis. Mdpi  Electronics  vol. 12, (9) 1989-1989.  
Cisuelo O, Stokes K, Oronti IB, Haleem MS, Barber TM, Weickert MO, Pecchia L and Hattersley J (2023). Development of an artificial intelligence system to identify hypoglycaemia via ECG in adults with type 1 diabetes: protocol for data collection under controlled and free-living conditions. Bmj Publishing Group  Bmj Open  vol. 13, (4) e067899-e067899.  
Andellini M, Haleem S, Angelini M, Ritrovato M, Schiaffini R, Iadanza E and Pecchia L (2023). Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol. Springer  Health and Technology  vol. 13, (1) 145-154.  

2022

Jossou TR, Tahori Z, Houdji G, Medenou D, Lasfar A, Sanya F, Ahouandjinou MH, Pagliara SM, Haleem MS and Et-Tahir A (2022). N-Beats as an EHG Signal Forecasting Method for Labour Prediction in Full Term Pregnancy. Mdpi  Electronics  vol. 11, (22) 3739-3739.  
Allocca C, Jilali S, Ail R, Lee J, Kim B, Antonini A, Motta E, Schellong J, Stieler L, Haleem MS, Georga E, Pecchia L, Gaeta E and Fico G (2022). Toward a Symbolic AI Approach to the WHO/ACSM Physical Activity & Sedentary Behavior Guidelines. Mdpi  Applied Sciences  vol. 12, (4) 1776-1776.  

2021

Haleem MS, Castaldo R, Pagliara SM, Petretta M, Salvatore M, Franzese M and Pecchia L (2021). Time adaptive ECG driven cardiovascular disease detector. Elsevier  Biomedical Signal Processing and Control  vol. 70,  
Langton S, Bannister J, Ellison M, Haleem MS and Krzemieniewska-Nandwani K (2021). Policing and Mental ill-health: Using Big Data to Assess the Scale and Severity of, and the Frontline Resources Committed to, mental ill-health-related calls-for-service. Oxford University Press (Oup)  Policing a Journal of Policy and Practice  vol. 15, (3) 1963-1976.  
Ellison M, Bannister J, Do Lee W and Haleem MS (2021). Understanding policing demand and deployment through the lens of the city and with the application of big data. Sage Publications  Urban Studies  vol. 58, (15) 3157-3175.  

2020

Lee WD, Haleem MS, Ellison M and Bannister J (2020). The Influence of Intra-Daily Activities and Settings upon Weekday Violent Crime in Public Spaces in Manchester, UK. Springer  European Journal On Criminal Policy and Research  vol. 27, (3) 375-395.  
Haleem MS, Do Lee W, Ellison M and Bannister J (2020). The ‘Exposed’ Population, Violent Crime in Public Space and the Night-time Economy in Manchester, UK. Springer Nature  European Journal On Criminal Policy and Research  vol. 27, (3) 335-352.  

2017

Haleem MS, Han L, Hemert JV, Li B, Fleming A, Pasquale LR and Song BJ (2017). A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis. Springer  Journal of Medical Systems  vol. 42, (1) 20-20.  
Soroka A, Liu Y, Han L and Haleem MS (2017). Big Data Driven Customer Insights for SMEs in Redistributed Manufacturing. Elsevier  Procedia Cirp  vol. 63, 692-697.  

2016

Haleem MS, Han L, Hemert JV, Fleming A, Pasquale LR, Silva PS, Song BJ and Aiello LP (2016). Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images. Springer  Journal of Medical Systems  vol. 40, (6) 132-132.  
Han L, Haleem MS and Taylor M (2016). Automatic Detection and Severity Assessment of Crop Diseases Using Image Pattern Recognition. Emerging Trends and Advanced Technologies For Computational Intelligence  Springer Nature   

2015

Haleem MS (2015). Automatic extraction of retinal features to assist diagnosis of glaucoma disease. 

2014

Haleem MS, Han L, van Hemert J, Li B and Fleming A (2014). Retinal area detector from scanning laser ophthalmoscope (SLO) images for diagnosing retinal diseases. Institute of Electrical and Electronics Engineers  Ieee Journal of Biomedical and Health Informatics  vol. 19, (4) 1472-1482.  
Haleem MS, Han L, van Hemert J, Li B and Fleming A (2014). Superpixel Based Retinal Area Detection in SLO Images. Computer Vision and Graphics  Springer Nature   

2013

Haleem MS, Han L, van Hemert J and Li B (2013). Automatic extraction of retinal features from colour retinal images for glaucoma diagnosis: A review. Elsevier  Computerized Medical Imaging and Graphics  vol. 37, (7-8) 581-596.