Farhan Akram

Erasmus MC — Netherlands

Computer Science · Physical Sciences

19h-index1.0kcitations76works0.82yr avg
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Research Topics

AI in cancer detection(24), Radiomics and Machine Learning in Medical Imaging(23), Medical Image Segmentation Techniques(20), Digital Imaging for Blood Diseases(7), Cutaneous Melanoma Detection and Management(6)

Publications77 total

Evaluating Open-Weight Large Language Models for Structured Data Extraction from Narrative Medical Reports Across Multiple Use Cases and Languages
arXiv (Cornell University)·2025· 1 citedOpen Access
From Reports to Relations: Large Language Models for Knowledge Graph Extraction in Digital Pathology
Lecture notes in computer science·2025
AB034. Weakly supervised artificial intelligence-based subtyping of thymic epithelial tumors using H&E whole slide images
Mediastinum·2025Open Access
Artificial intelligence for diagnosis and prognosis of thymic epithelial tumors: a systematic review
Mediastinum·2025· 1 citedOpen Access
Deep Learning-based Weapon Detection using Yolov8
International Journal of Innovations in Science and Technology·2025· 1 citedOpen Access
Deep Learning–Based Retinoblastoma Protein Subtyping of Pulmonary Large-Cell Neuroendocrine Carcinoma on Small Hematoxylin and Eosin–Stained Specimens
Laboratory Investigation·2025· 2 citedOpen Access
A0682 – BMolNet identifies molecular subtypes linked to bacillus Calmette-Guerin response from bladder cancer histology images
European Urology·2025
AB037. AI-powered differentiation of thymomas (A and B3) and thymic carcinoma using histopathological analysis of H&E whole slide images
Mediastinum·2024Open Access
Prediction of molecular subclasses of uveal melanoma by deep learning using routine haematoxylin–eosin‐stained tissue slides
Histopathology·2024· 5 citedOpen Access
Abstract B004: Deep learning unveils molecular footprints in histology: predicting molecular subtypes from bladder cancer histology slides
Clinical Cancer Research·2024
Deep learning unveils molecular footprints in histology: Predicting molecular subtypes from bladder cancer histology slides
European Urology·2024
Synthesis-Guided Unsupervised Anomaly Detection and Analysis with GPT in Industrial Images
SSRN Electronic Journal·2024Open Access
Artificial intelligence-based recurrence prediction outperforms classical histopathological methods in pulmonary adenocarcinoma biopsies
Lung Cancer·2023· 8 citedOpen Access
Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review
Cancers·2023· 20 citedOpen Access
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review
arXiv (Cornell University)·2023Open Access
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review
2023· 2 citedOpen Access
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review
2023· 5 citedOpen Access
The value of prognostic and predictive parameters in early-stage lung adenocarcinomas: A comparison between biopsies and resections
Lung Cancer·2022· 7 citedOpen Access
Efficient Breast Cancer Classification Network with Dual Squeeze and Excitation in Histopathological Images
Diagnostics·2022· 26 citedOpen Access
Self-initialized active contours for microscopic cell image segmentation
Scientific Reports·2022· 10 citedOpen Access
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Frequent Co-authors

Domènec Puig(22), Md. Mostafa Kamal Sarker(21), Hatem A. Rashwan(20), Vivek Kumar Singh(19), Santiago Romaní(15), Nidhi Pandey(13), Adel Saleh(11), Kwang Nam Choi(11), Mohamed Abdel‐Nasser(10), Saddam Abdulwahab(8), Syeda Furruka Banu(6), Petia Radeva(6), Jeong Heon Kim(6), Forhad Uddin Hasan Chowdhury(5), Miguel Ángel García(5), Antonio Miguel(5), Meritxell Arenas(5), Hwee Kuan Lee(4), Teodora E Trandafir(4), Jan H. von der Thüsen(4)