{"componentChunkName":"component---src-templates-person-person-tsx","path":"/person/Jamal-Hossain-1b53705d-0804-4d18-90fb-04fe1d99c1f0/","result":{"data":{"person":{"id":"1b53705d-0804-4d18-90fb-04fe1d99c1f0","profilePicture":"https://research-information.bris.ac.uk/ws/files/495367075/Profile_Picture_Jamal_AI.jpeg","profileType":"ACADEMIC","title":"Dr","firstName":"Jamal","lastName":"Hossain","addresses":[{"firstLine":"Level 7","secondLine":"Bristol Royal Infirmary","thirdLine":"Marlborough Street","fourthLine":"Bristol","fifthLine":null,"postCode":"BS2 8HW","country":null}],"socialMedia":[],"expertiseTags":["Applied health statistics","Survival analysis","Quality of life","Cancer survivorship","Explainable artificial intelligence","Health services research","Machine learning","Multilevel modelling","Prediction modelling","Longitudinal data analysis"],"biography":"Dr Jamal Hossain is a Senior Lecturer in Applied Health Statistics at the University of Southampton and an Honorary Research Associate at Bristol Medical School, University of Bristol. He has an academic background in statistics, social statistics and demography, with a PhD from the University of Southampton. <br /><br />His work involves applying statistical methods to multidisciplinary health and healthcare research, working closely with clinicians, health researchers and other methodological specialists. He contributes statistical expertise to a range of collaborative studies, including NIHR-funded research, and has experience supporting the design, analysis and interpretation of observational, longitudinal and health services research.<br /><br />At Bristol, he contributes to collaborative research involving the National Child Mortality Database and the QUINTET programme, with a particular focus on quantitative analysis. Alongside his research, he is involved in postgraduate teaching, research supervision and methodological support, and contributes to the development of quantitative research capacity across interdisciplinary health research teams.","postNominals":null,"websiteLink":null,"email":"jamal.hossain@bristol.ac.uk","telephone":[],"snippet":"I use statistics, epidemiology and data science to answer health research questions, analyse complex patient data and develop prediction models that support better healthcare decisions and outcomes.","teaching":null,"researchInterest":"<p>My research interests focus on applied health statistics, epidemiology and quantitative health research. I have particular interests in longitudinal and multilevel modelling, prediction modelling, machine learning and explainable AI, survival analysis, causal inference, and the analysis of routinely collected and large-scale health data. My applied research spans cancer survivorship and quality of life, child health, health inequalities, healthcare utilisation and health services research. I am particularly interested in developing and applying robust statistical and data-driven methods to support clinical decision-making, risk prediction and improved patient outcomes.</p>","relatedPeople":[],"positions":{"external":[],"internal":[{"role":"Honorary Research Associate","organisation":"Bristol Medical School","url":"http://www.bristol.ac.uk/medical-school/","tag":"School","active":true}]},"publications":{"total":"0","linkToPublications":"https://research-information.bris.ac.uk/en/persons/jamal-hossain/publications/","all":[],"highlighted":[]},"thesis":null,"researchProjects":{"total":0,"linkToProjects":"https://research-information.bris.ac.uk/en/persons/jamal-hossain/projects/","projects":[]},"thesisSupervisions":{"total":0,"linkToSupervisions":null,"supervisions":[]}},"site":{"siteMetadata":{"title":"Our People"}}},"pageContext":{"id":"1b53705d-0804-4d18-90fb-04fe1d99c1f0","profileType":"ACADEMIC","firstName":"Jamal","lastName":"Hossain","title":"Dr","profilePicture":"https://research-information.bris.ac.uk/ws/files/495367075/Profile_Picture_Jamal_AI.jpeg","postNominals":null,"email":"jamal.hossain@bristol.ac.uk","embedded":false,"featureToggles":{"research":true,"researchProjects":true,"thesisSupervisions":true,"thesis":true,"allPositions":true,"searchFilters":true}}},"staticQueryHashes":["2510609168","3397900109"]}