Dr Mintu Nath

Dr Mintu Nath
Dr Mintu Nath

Dr Mintu Nath

MSc, PhD, FHEA

Senior Lecturer

Accepting PhDs

About

The University of Aberdeen

Medical Statistics Team

Institute of Applied Health Sciences

Room 1:004 Polwarth Building

Foresterhill

University of Aberdeen

Aberdeen

AB25 2ZD

Biography

Before joining the University of Aberdeen, I worked as a Senior Statistician with Biomathematics and Statistics Scotland, and later as a Senior Biomedical Statistician with the University of Leicester. Broadly, my research, consultancy and teaching focussed in the areas of statistical genetics, genetic epidemiology and applied statistics particularly those involving high-volume and high-dimensional datasets.

Memberships and Affiliations

Internal Memberships

Member of the University Senate

Member of the University Research Culture Group

Member of Postgraduate Teaching Task and Finish Group

 

External Memberships

Fellow of the Royal Statistical Society

Honorary Contract of the NHS Grampian

Honorary Lecturer of the University of Leicester

Research

Research Overview

My research interests include exploring and integrating diverse resources of large patient cohorts - comprising of anthropometric, clinical, genetic and multi-omics data - to develop predictive models to evaluate the risk of important diseases.

Research Areas

Accepting PhDs

I am currently accepting PhDs in Applied Health Sciences, Biomedical Sciences.


Please get in touch if you would like to discuss your research ideas further.

Email Me

Applied Health Sciences

Supervising
Accepting PhDs

Biomedical Sciences

Supervising
Accepting PhDs

Research Specialisms

  • Biomedical Sciences
  • Machine Learning
  • Health Informatics
  • Applied Statistics
  • Medical Statistics

Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is HESA open data, published under the Creative Commons Attribution 4.0 International licence.

Current Research

Using multi-dimensional eye-tracking data (saccade) to develop predictive models for diagnosing and managing major mental illness

Funded by the NHS Grampian Endowment award and Miller Mackenzie Trust, we are implementing machine learning tools to develop predictive models of mental health conditions using multi-dimensional eye-tracking data. 

Mathematical and statistical evaluation of Positron Emission Tomography (PET) data for the management of cancer

I am collaborating with Prof Professor Andy Welch at the University of Aberdeen on the application of mathematical and statistical tools to analyse PET data for detecting pathophysiological changes in different tissues. We are currently supervising two PhD students. 

SHERLOCK - An observational Study on HEalthcare Resource utiLisation related to exacerbatiOns in patients with COPD

Using multiple sources and high-volume population data of primary care patients affected with Chronic Obstructive Pulmonary Disease (COPD), the project investigates the associations between the history of exacerbations with the frequency and rate of future exacerbations as well as healthcare resource utilisation (HCRU) cost. There is a PhD opportunity to develop predictive models using linked electronic health records in a machine learning framework to assess the risk of moderate and severe exacerbations in Chronic Obstructive Pulmonary Disease (COPD). Contact me if you are interested.

BIOSTAT-CHF - BIOlogy Study to TAilored Treatment in Chronic Heart Failure

BIOSTAT-CHF is a Consortium of 11 European countries, funded by an FP7 Health grant from the European Union. I am leading the work to develop a comprehensive bioinformatics and statistical analysis workflow for analysing high-resolution array GeneChip® Human Transcriptomic Array 2.0 data in collaboration with the team at the University of Leicester and the EU partner organisations. 

The Optical Coherence Tomography (OCT) of the retinal layers and its association with the retinal pathophysiology in infants

I am collaborating with the researchers at the University of Leicester to develop comprehensive statistical models to analyse foveal and retinal morphological data in preterm infants. We are developing a data-driven approach to understand the dynamics of retinal development in neonatal babies and its association with the retinopathy of prematurity using OCT data.

Collaborations

Can deep learning help improve automated retinal image analysis algorithms for diabetic retinopathy screening?

I am collaborating with clinicians and scientists at the NHS and University of Aberdeen for developing and optimising deep learning algorithms to automate the assessment of retinal features associated with diabetic retinopathy. 

Data-driven design, monitoring, and adaptation of COVID and non-COVID clinical care pathways

We are using real-time as well as historical data to understand the healthcare utlilisation of people shielding during COVID-19 as well as affected by the disease. The project is funded by NHS Endowment Research Grant and Scottish Government Chief Scientist Office. 

The UK-REBOA (Resuscitative Endovascular Balloon Occlusion of the Aorta) Trial

Funded by NIHR, I am collaborating with clinicians and scientists to develop methodologies for the elicitation of experts' probabilities in the context of randomised control trial. 

Investigating socioeconomic disparities as a cause and consequence of deteriorating kidney health among people admitted to hospital with an acute illness

The project aims to establish the relationship between socioeconomic status and health outcomes among people leaving hospitals with and without acute kidney injury (AKI). The project will also explore the feasibility and added value of including individual level (census) socioeconomic measures in clinical risk tools for predicting adverse health outcomes. 

Supervision

My current supervision areas are: Applied Health Sciences, Biomedical Sciences.

Current PhD Projects

Mathematical and statistical evaluation of Positron Emission Tomography (PET) data for cancer management (Supervisor)

The potential value of Positron Emission Tomography (PET) radiomics to predict hypoxia and survival rate (Co-supervisor)

Predicting cardiotoxicity post-cardiotoxic chemo and biological therapies (Co-supervisor)

Understanding the determinants of children's mental health trajectories (Co-supervisor)

Study on prevalence and geographical distribution of endometriosis-like symptoms in the UK (Co-supervisor)

 

Teaching

Teaching Responsibilities

I undertake teaching and training programs in Statistics for MSc and PhD students. I also conduct statistical consultancies for students as well as the University and NHS staff. I am interested to develop user-friendly and interactive applications to enhance the learning of statistical principles. I provide a range of R courses for the University staff and Doctoral students.

Applied Statistics Course

I teach different statistical courses organised by the Medical Statistics team:

  • MSc Course: Applied Statistics (PU5017)
  • MSc Online course: Applied Statistics (PU5522)
  • Intermediate Medical Statistics for University staff and postgraduate students
  • Other statistics courses as part of the Medical Statistics Team

ABACUS - Apps Based Activities for Communicating and Understanding Statistics

ABACUS is a set of R Shiny apps for effective communication and understanding of statistics. The current version includes explaining properties of the normal distribution, properties of the sampling distribution, one-sample z and t-tests, two samples independent (unpaired) t-test and analysis of variance. Check the ABACUS website and explore it. We will be adding new modules in future. Please visit again for more updates.

ABACUS on CRAN

ABACUS is also available as an R package on the Comprehensive R Archive Network (CRAN). Please download ABACUS from the CRAN package repository.

iDRUG: interactive Dose-Response User Guide

With fundings from the British Pharmacological Society, I am collaborating with Prof Steven Tucker at the University of Aberdeen to develop a simple, interactive and user-friendly application to conduct dose-response analysis in Pharmacology settings. The iDRUG website is live now. Watch a demonstration of iDRUG here. Further development of iDRUG is in progress. Watch this space for further details!

R Courses

I developed and presented an extensive array of introductory and advanced R courses as well as statistical analysis in the R software environment. If you are interested to organise bespoke R courses for your staff, I will be happy to help. Please contact me with the details of your request.

Publications

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