activity
20202026
most citedA Review of Mathematical and Computational Methods in Cancer Dynamics

41 citations · 139 across the 17 of their papers we have counts for

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6 papers · 1 filter

q-bio.QM2025

Exhaustive Investigation of CBC-Derived Biomarker Ratios for Clinical Outcome Prediction: The RDW-to-MCHC Ratio as a Novel Mortality Predictor in Critical Care

Dmytro Leontiev, Abicumaran Uthamacumaran, Riya Nagar +1

Ratios of common biomarkers and blood analytes are well established for early detection and predictive purposes. Early risk stratification in critical care is often limited by the…

q-bio.QM2025

Complexity-Informed Causal Modeling of Neurodevelopmental Trajectories in Pediatric High-Grade Gliomas: Divergences from Neural Stem Cell Signatures

Abicumaran Uthamacumaran, Hector Zenil

Pediatric high grade gliomas are lethal evolutionary disorders with stalled developmental trajectories and disrupted differentiation hierarchies. We integrate transcriptional and a…

q-bio.QM2025

Neurosymbolic Learning for Predicting Cell Fate Decisions from Longitudinal Single Cell Transcriptomics in Paediatric Acute Myeloid Leukemia

Abicumaran Uthamacumaran, Hector Zenil

Paediatric Acute Myeloid Leukemia is a complex adaptive ecosystem with high morbidity. Current trajectory inference algorithms struggle to predict causal dynamics in AML progressio…

q-bio.QM2025★ 4 cited

AI-Driven Hybrid Ecological Model for Predicting Oncolytic Viral Therapy Dynamics

Abicumaran Uthamacumaran, Juri Kiyokawa, Hiroaki Wakimoto

Oncolytic viral therapy (OVT) is an emerging precision therapy for aggressive and recurrent cancers. However, its clinical efficacy is hindered by the complexity of tumor-virus-imm…

q-bio.QM2023★ 1 cited

Integrative Adaptive Indexes from Noisy Routine Haematological Markers can Predict and Discriminate Health Status and Biological Age

Santiago Hernández-Orozco, Abicumaran Uthamacumaran, Francisco Hernández-Quiroz +2

For more than two decades, advances in personalised medicine and precision healthcare have largely been based on genomics and other omics data. These strategies aim to tailor inter…

q-bio.QM2022★ 24 cited

Machine Intelligence-Driven Classification of Cancer Patients-Derived Extracellular Vesicles using Fluorescence Correlation Spectroscopy: Results from a Pilot Study

Abicumaran Uthamacumaran, Mohamed Abdouh, Kinshuk Sengupta +5

Patient-derived extracellular vesicles (EVs) that contains a complex biological cargo is a valuable source of liquid biopsy diagnostics to aid in early detection, cancer screening,…