Explore my coding projects and developed products…
A machine learning-based clinical scoring system designed to predict hypoalbuminemia risk following One-Anastomosis Gastric Bypass (OAGB) surgery, enabling early intervention and personalized patient care.
SnapExplain is an Android utility that brings large language model (LLM) explanations directly into your reading workflow.It integrates with Android’s native text-selection menu, allowing users to highlight any sentence in a PDF, ebook, or article and receive an instant, contextual explanation — without leaving the app they’re reading in.
A retrieval-augmented generation (RAG) system that uses the ASMBS bariatric surgery textbook as a knowledge base to answer medical questions with higher accuracy and fewer hallucinations than general-purpose AI models.
A data-driven project that models long-term postoperative weight trajectories after bariatric surgery and translates these patterns into clinically interpretable, patient-level predictions.
A deep learning–based framework for intelligent extraction, semantic understanding, and structured digitization of Persian medical documents, designed to automate health insurance workflows and fraud detection.
An M.D. thesis project investigating structural neuroimaging correlates of cognitive impairment in frontotemporal dementia (FTD), with a focus on extracting meaningful information from low-resolution routine clinical MRI data.
A comprehensive systematic review and meta-analysis examining how metabolic and bariatric surgery (MBS) affects serum uric acid over time, and how these changes relate to renal function and visceral adiposity.
A cross-sectional clinical study examining presentation patterns, diagnostic delays, and treatment outcomes in patients with pemphigus vulgaris, highlighting systemic barriers to early diagnosis.
A pilot study evaluating whether computer vision can replace subjective visual estimation of biliopancreatic limb (BPL) length during gastric bypass surgery with objective, calibrated intraoperative measurements.
A neuroimaging study investigating how hippocampal subfield structure and shape differ across ApoE genotypes, using high-resolution MRI and computational geometry–based morphometric analysis.
An ongoing research effort to improve brain MRI reconstruction techniques, enabling large-scale neurodegeneration studies using routine clinical imaging data rather than relying solely on high-resolution research scans.