We are proud to share that Abdul Rehman Akbar, a Graduate Research Associate in the AI4Path Lab, has been awarded a prestigious Travel Award by the Digital Pathology Association (DPA) to attend PathVisions 2025, taking place October 5–7 in San Diego, California.

This highly competitive award recognizes outstanding early-career researchers and supports their participation in one of the world’s leading conferences in digital pathology and AI.

✈️ What the Award Covers

As a Travel Award recipient, Abdul will receive:

✅ Full conference registration (complimentary)
🏨 Hotel accommodation at the Manchester Grand Hyatt
🛫 Round-trip airfare, with travel expenses fully covered
💼 The opportunity to present his accepted abstract and engage with leaders in computational pathology

This award enables promising trainees like Abdul to share their work, build meaningful collaborations, and gain exposure to the latest innovations in the field.

👏 Congratulations!

Please join us in congratulating Abdul on this exciting achievement! His dedication and innovation continue to embody AI4Path’s mission to advance patient-centered, AI-powered digital pathology.

We’re thrilled to see Abdul represent the lab on the national stage and look forward to his continued contributions to computational pathology and precision oncology.

📍 Stay tuned for more updates from AI4Path at PathVisions 2025!

The AI4Path Lab is growing! We’re excited to announce the arrival of eight new members joining us this fall, bringing fresh ideas, perspectives, and energy to our mission of transforming cancer diagnosis and treatment through artificial intelligence and computational pathology.

🎓 Meet Our New PhD Students

We’re proud to welcome three outstanding PhD students who will be pursuing their doctoral research under the mentorship of Dr. Khalid Niazi and the broader AI4Path team:

• Yixin (James) Chen
• Tianyang Wang
• Alejandro Leyva

🌍 Welcoming Our Visiting Students

We’re also delighted to host five visiting students who will be contributing to ongoing research projects over the next few months:

• Yuhang Kang
• Makoto Kawamoto
• Muneeb Khan
• Alaa Abukaresh
• Charles Rabolli

🚀 Growing Together

At AI4Path, we believe that science thrives through collaboration, curiosity, and shared purpose. This new cohort of students represents the next generation of innovators in digital pathology and AI-driven precision medicine.

We’re thrilled to welcome each of them to the team and can’t wait to see what we’ll accomplish together.

We’re thrilled to announce that Dr. Muhammad Khalid Khan Niazi, Dr. Anna Vilgelm, and Dr. Arya Mariam Roy have been awarded a prestigious Intramural Research Program (IRP) 2025 Grant, funded by Pelotonia! Their project, titled:

Leveraging AI and Digital Pathology to Guide Precision Therapy for Metastatic Hormone Receptor–Positive, HER2‑Negative Breast Cancer

has received support for a pilot research effort aimed at transforming the treatment of metastatic HR‑positive, HER2‑negative breast cancer.

🎯 Why This Grant Matters

IRP funding, provided through Pelotonia-supported initiatives at OSUCCC – James, is designed to catalyze early translational studies by seeding innovative ideas that may evolve into large-scale funded projects.
This award reflects the innovation and competitiveness of their proposal—focused on integrating AI methods and whole‑slide histopathology images to inform precision therapy decisions in metastatic breast cancer.

🔍 About the Project

The funded study aims to:

• Employ computational pathology and AI algorithms to analyze tumor morphology and microenvironment features from digital H\&E images.
• Identify spatial and morphological biomarkers predictive of therapeutic response in metastatic HR-positive, HER2-negative breast cancer—an area with limited targeted therapy options.
• Generate preliminary data to support future translational work and potential NCI funding proposals.

🎉 What’s Next

• This IRP grant will launch the initial phase of the project, focusing on data collection, model development, and validation.
• Results from this pilot work will form the backbone of future funding applications and collaborative efforts aimed at improving therapy selection and outcomes for breast cancer patients.
• Follow our blog for future updates on milestones, publications, and collaborative opportunities stemming from this award.

🙏 Thank You, Pelotonia!

We extend our deepest gratitude to the Pelotonia community, whose collective fundraising fuels vital research at OSUCCC – James. Because of their support, early-career investigators like our team can pursue bold, life-changing projects designed to end cancer.

Join us in congratulating Dr. Niazi, Dr. Vilgelm, and Dr. Roy! This IRP award is a significant milestone in their journey to bring AI-driven, pathology‑based precision medicine to patients with metastatic HR‑positive, HER2‑negative breast cancer.

Stay tuned for scientific updates and follow us for more breakthroughs from the AI4Path Lab.

We’re excited to share that Hikmat Khan, a postdoctoral scholar in the AI4Path Lab, has been selected as a 2025 Trainee Travel Award recipient by the Digital Pathology Association (DPA)! This prestigious award will support his participation at PathVisions 2025: From Pixels to Patients, held October 5–7 in San Diego, CA 🏖️.

🌟 Why This Matters

This award recognizes Hikmat’s outstanding contributions to AI in computational pathology and his potential to further innovation through the AI4Path Lab. As one of only six trainees selected nationally, Hikmat joins an inspiring cohort invited to share their work and engage with leaders in digital pathology and AI.

Hikmat’s accepted abstract at PathVisions 2025 will showcase one of AI4Path’s recent studies—stay tuned for more information on this and other exciting presentations!

🎤 At the Conference

As part of the Trainee Travel Award activities, Hikmat will:

• Present his abstract at the conference
• Attend the full program, including opening and closing ceremonies
• Participate in networking events and the DPA President’s Dinner on October 4
• Be featured on DPA’s social media channels and website throughout the conference.

🙏 Thank You, DPA!

We’re immensely grateful to the Digital Pathology Association for their support of emerging researchers like Hikmat and for fostering the next generation of leaders in digital and computational pathology.

📣 Looking Forward

Join us in congratulating Hikmat on this achievement! We’re proud to have representation from the AI4Path Lab at PathVisions 2025 and look forward to sharing scientific highlights and connections made during the event.

If you’d like to meet him or other AI4Path team members in San Diego, please reach out—we’d love to connect!

We are excited to announce that three cutting-edge AI-driven studies from the AI4Path Lab have been accepted for presentation at PathVisions 2025, the premier global conference on digital pathology and AI, taking place October 5–7 in San Diego.

📝 Accepted Abstracts

1. AI-Based Detection of FGFR Mutations from H\&E Whole‑Slide Images in Cholangiocarcinoma
This study explores how deep learning can non-invasively predict fibroblast growth factor receptor (FGFR) mutations directly from H\&E-stained slides of cholangiocarcinoma, potentially guiding targeted therapy decisions in otherwise resource-limited settings.

2. AI-Powered Recurrence Risk Prediction in Invasive Lung Adenocarcinoma Using H\&E Images
This abstract presents a predictive model that stratifies patients by recurrence risk following resection of lung adenocarcinoma, with the goal of supporting personalized surveillance and adjuvant therapy planning.

3. AI-Based Quantification of Histopathological Patterns in Invasive Lung Adenocarcinoma
Here, our team develops automated methods to quantify tissue architectural patterns—such as lepidic, acinar, and solid components—in lung tumors, facilitating standardization and improving prognostic accuracy.

Why These Studies Stand Out

🌟 PathVisions 2025 brings together over 800 experts in AI and digital pathology to drive innovations from pixels to patients through real-world applications. Having three abstracts accepted into the poster track underscores the recognition of our lab’s leadership in harnessing AI for clinically relevant pathology workflows.

💬 Join Us in San Diego!

We look forward to sharing our AI4Path research at PathVisions 2025 and discussing how these models can inform future clinical and translational studies. Stay tuned for updates on poster numbers and presentation schedules.

If you’d like to connect or collaborate at the conference, feel free to reach out—we’d love to meet up!

We’re thrilled to share that a new study from the AI4Path Lab, led by Dr. Muhammad Khalid Khan Niazi, has been accepted and published in Cancers (MDPI) under the Cancer Informatics and Big Data section. 🎉

📖 Paper Title:
Predicting Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic Images
🔗 Read the full article

🔍 What’s the Study About?

Triple-negative breast cancer (TNBC) is one of the most aggressive and difficult-to-treat subtypes of breast cancer, lacking hormone receptor and HER2 targets. While neoadjuvant chemotherapy (NACT) remains the mainstay of treatment, not all patients respond, leading to unnecessary toxicity without benefit.

This study tackles a key clinical question:

Can we predict chemotherapy response before treatment begins—using only routine biopsy slides?

🧠 AI-Powered Predictive Modeling

Our team developed an attention-based multiple instance learning (MIL) model that uses standard hematoxylin and eosin (H\&E)-stained biopsy images to predict pathologic complete response (pCR) to NACT in TNBC patients.

Key Results:

• 📊 Internal AUC: 0.85 (cross-validation on 174 cases)
• 🌍 External AUC: 0.78 (validated on an independent cohort of 30 cases)
• 🔬 Interpretability: High-attention regions aligned with immune-rich tumor areas, especially those enriched in CD8+ T cells, CD163+ macrophages, and PD-L1 expression.

These findings suggest that biologically meaningful features—particularly immune-related components—can be captured from H\&E slides and used to personalize treatment in TNBC.

💡 Why It Matters

This study highlights the growing potential of AI to:

• ✅ Predict treatment response from pre-treatment data
• ✅ Reduce unnecessary toxicity from ineffective therapy
• ✅ Personalize care pathways in aggressive cancers like TNBC
• ✅ Bridge the gap between routine pathology and precision oncology

The integration of multiplex immunohistochemistry (mIHC) data further strengthens the biological relevance and clinical interpretability of the model—an essential step for translational impact.

🧪 Meet the Authors

This collaborative project brought together experts from:

• The Ohio State University (AI4Path Lab)
• University of Rochester Medical Center
• Brown University
• University of Alabama at Birmingham

Lead Author: Hikmat Khan
Senior Author & PI: Dr. Muhammad Khalid Khan Niazi (Director, AI4Path Lab)

🔗 Reference:
Khan, H., Su, Z., Zhang, H., Wang, Y., Ning, B., Wei, S., Guo, H., Li, Z., & Niazi, M.K.K. (2025). Predicting Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic Images. Cancers, 17(15), 2423. https://doi.org/10.3390/cancers17152423

📣 Stay tuned for more cutting-edge research from AI4Path, where we’re redefining what’s possible in computational pathology.

Date of Event: Thursday, July 24
Event Type: Virtual Seminar
Host: Wake Forest Center for Artificial Intelligence Research (CAIR)
Speaker: Dr. Muhammad Khalid Khan Niazi, Director of AI4Path Lab and Associate Professor of Pathology, The Ohio State University

This past Thursday, July 24th, Dr. Khalid Niazi delivered an insightful talk as part of the Artificial Intelligence in Action seminar series hosted by Wake Forest’s Center for Artificial Intelligence Research (CAIR). The seminar, titled “Prognostic and Predictive Models in Pathology,” attracted clinicians, researchers, and AI enthusiasts eager to understand the evolving role of artificial intelligence in cancer diagnostics and treatment planning.

Dr. Niazi, a leading voice in computational pathology and director of the AI4Path Lab, explored how predictive models—particularly those trained on histopathology images—can revolutionize clinical decision-making. He emphasized the limitations of current foundation models when applied to pathology, advocating instead for the development of histology-informed AI frameworks that are not only accurate but clinically robust.

Dr. Niazi’s seminar was a compelling reminder that AI in pathology is not just about accuracy—it’s about clinical impact. As the field advances, collaboration between data scientists, pathologists, and clinicians will be essential to turn promising models into trusted medical tools.