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Using Artificial Intelligence to Find the Optimal Margin Width in Hepatectomy for Colorectal Cancer Liver Metastases

Dimitris Bertsimas, ..., Seehanah Tang, ...

Published in JAMA Surgery, 2022

An AI-driven analysis identifying optimal surgical margin widths in hepatectomy for colorectal cancer liver metastases to improve long-term oncologic outcomes.

An interpretable AI model for recurrence prediction after surgery in gastrointestinal stromal tumour: an observational cohort study

Dimitris Bertsimas, Georgios Antonios Margonis, Seehanah Tang, Angelos Koulouras, Cristina R. Antonescu, ...

Published in Lancet eClinicalMedicine, 2023

An interpretable AI model predicting recurrence risk after surgical resection of gastrointestinal stromal tumors, designed to support personalized post-operative surveillance and treatment planning.

Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study

Dimitris Bertsimas, ..., Seehanah Tang, ...

Published in Lancet Oncology, 2024

An interpretable AI model to guide adjuvant imatinib treatment decisions after resection of localized gastrointestinal stromal tumors, validated in a large multi-institutional cohort.

Towards Better Clinical Risk Scores with AnnealScore: A Residual-Guided Simulated Annealing Algorithm

Hannah Eglinton, Seehanah Tang, Tongtong Zhao, Yu Yan, Alice Paul

Submitted to International Journal of Biostatistics · revise & resubmit

A residual-guided simulated annealing algorithm for building sparse, interpretable clinical risk scores, improving on existing integer risk-scoring methods.

Plasma Proteomics for Unified Multi-Disease Diagnostics and Multi-Horizon Prognostics

Seehanah Tang, Cindy Beini Wang, Carol Gao, Dewang Agarwal, Joanna G. Kondylis, Dimitris Bertsimas

In preparation, 2026

A unified plasma-proteomic model for multi-disease diagnosis and multi-horizon prognosis, aiming to enable earlier and more precise disease detection from a single blood draw.

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