My research focuses on developing novel solutions for clinical problems using the power of digital technologies. I am mainly interested in developing multimodal machine-learning models that can improve clinical practice for clinicians and healthcare delivery for patients.
I had the opportunity to work with some of the best researchers and faculty members in several research centers during my j
I am leading the " Artificial Intelligence in Medical Sciences Association", which is a research group in my university with the mission of conducting research projects in the field of clinical applications of artificial intelligence. You can learn about our group activities here
https://aimstums.ir .
Digital Health Translational Research
DelShad
a cross-platform app preventing cardiovascular disease using personalized guideline-based recommendations, as part of a nationwide initiative aimed at reaching more than 10 million citizens.
This app was developed at Cardiovascular Research Institution at Tehran Heart Center, the leading cardiology academic center in Iran. It is supported by Tehran City Municipality.
https://delshad.tums.ac.ir
VIZIT
A Comprehensive platform for visualizing medical data, tailored for large medical studies with numerous variables.
This platform is the result of a collaboration between the Iranian National Health Institute and the Non-Communicable Disease Research Center to help decision-makers and researchers understand the finding of large population studies due to the complex relationship between different variables.
https://vizit.tums.ac.ir
CovidBoard
An online interactive dashboard to track and visualize the latest information about the COVID-19 pandemic.
This project was developed during the first months of the pandemic with the help of some faculty members and researchers at the School of Public Health at Tehran University of Medical Sciences.
https://covidboard.aljasem.eu.org/
Kamaryar
an online chatbot that helps users to control their back pain by providing custom exercises tailored based on user profiles.
This AI-based chatbot was developed in the Sports Medicine Research Center at Tehran University of Medical Sciences, and it supports many platforms so it can be accessed with ease through different devices.
https://kamaryar.tums.ac.ir
PyCVDRisk
An open-source Python package that helps ease calculating cardiovascular risk scores using different methods.
This package is designed to help researchers and data scientists to use these CVD risk calculators with large datasets. This project was developed to study the distribution of cardiovascular risk factors and CVD risk in Iran at the National Institute of Health Research.
https://pycvdrisk.aljasem.eu.org/
BioMedical vLab
A cross-platform metaverse platform to create a collaborative and engaging virtual learning environment for medical sciences.
This project was developed during the COVID-19 pandemic to help students to attend practical laboratory sessions online. This project runs smoothly on a wide range of devices, including smartphones, tablets, and VR Headsets.
https://vlab.aljasem.eu.org/
OpenMedicalData Collabration
A repository to collect, share and access medical and clinical data in an easy-to-access way to help AI researchers to focus on the development of new AI models.
I started this project after noticing that finding the right dataset to train clinical AI models is not an easy task. This project is opensource and free to use.
https://OpenMedicalData.github.io
ENZAIR
A web-based application that uses deep learning to analyze brain MRI Scans to predict developing dementia .
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SimpleStats
A web-based statistical package that runs directly from a web browser powered by WebAssembly implementation of R-Language.
It can be used to do all sorts of biomedical statistical calculations with a simple and user-friendly interface.
http://ssc.tums.ac.ir/
Breast Cancer Awareness
A Mobile app to increase awareness of breast cancer and help women at risk understand the early symptoms of the disease.
This app is currently under development in collaboration with the oncology research center at Sharati Hospital, one of the leading academic clinical centers in the region.
AI Research
CXR Pneumonia Detection
Chest X-Rays are one of the most common imaging modalities used in clinical settings due to their low cost and the valuable insights it provides to clinicians. However, the shortage of specialist doctors in different parts of the world, makes it difficult to detect and prioritize patients who need faster clinical attention.
This AI model was trained on different types of pneumonia cases and achieved acceptable sensitivity and specificity, making it a handy tool for screening Chatst X-Ray Scans.
Bone Age Calculator
Many children in the 3rd world countries are malnourished, which might affect their growth rate. Giving a complete assessment plan to help the affected children have normal growth requires some laboratory testing and a wrist x-ray to estimate the biological age, compared to age based on the date of birth.
This project act as a powerful clinical decision-making support tool in primary care settings by helping identify the biological age based on the wrist X-ray scan.
Diabetic Retinopathy Screening
Diabetes is one common health problem that affects millions around the world. Unfortunately, many of the patients know about their condition after the disease becomes symptomatic.
One of the most important complications of diabetes is diabetic retinopathy, which is the leading cause of preventable blindness globally. this model helps in the early detection and screening of this condition by only uploading simple pictures.
Skin Cancer Scanner
Skin cancer is one of the most common types of cancer globally. It affects a wide range of age groups and if not detected and treated in early stages, it can be lethal.
This model was trained using thousands of images taken for different skin lesions, and it can identify suspicious skin lesions that might need further diagnostic actions.
ECG Arrhythmia Detection
Electrocardiogram is one of the most used modalities in clinical practice to assess the functional activities of the heart. Reading and interpreting electrocardiograms or ECG charts can sometimes be difficult.
this simple AI model can identify the common arrhythmia cases, which can be used as a valuable clinical decision support tool in areas where professional cardiologists might not be accessible.
COVID-19 CT Scan Detection
The COVID-19 pandemic was one of the biggest challenges facing the world in modern history. The high number of patients and the shortage in numbers of healthcare professionals as well as PCR testing sometimes can be misleading to detect active cases.
CT Scans are one of the most used imaging modalities in clinical practice for their ease of use, and abundant clinical insights they provide. This model can help in detecting suspected case using ct scans which can be valuable during this pandemic.
Heart Failure Prediciton
Heart Failure is a condition where that occurs when the heart muscle doesn't pump blood as well as it should. Many underlying health conditions can lead to heart failure.
this model was trained using open-source data and was able to predict the probability of developing heart failure, which can be used in real-life scenarios to evaluate patients ho at risk and provide them with necessary interventions to stop the worsening o their cases.
Heart Attack Prediction
A heart attack (myocardial infarction or MI) is a serious medical emergency in which the supply of blood to the heart is suddenly blocked. Heart attack is one of the leading causes of mortality around the world.
This model can provide critical insights about the patients who might be at risk of MI soon, so healthcare professionals can do life-saving preventive measures for the patients.
Brain Stroke Predection
An ischemic stroke occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissue from getting oxygen and nutrients. Brain cells begin to die in minutes.
A stroke is a medical emergency, and prompt treatment is crucial. Early action can reduce brain damage and other complications.