Insights from recent episode analysis
Audience Interest
Podcast Focus
Publishing Consistency
Platform Reach
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Most discussed topics
Brands & references
Total monthly reach
Estimated from 25 chart positions in 25 markets.
By chart position
- 🇨🇦CA · Natural Sciences#1395K to 30K
- 🇰🇷KR · Natural Sciences#2530K to 100K
- 🇸🇪SE · Natural Sciences#2930K to 100K
- 🇯🇵JP · Natural Sciences#9910K to 30K
- 🇮🇳IN · Natural Sciences#1081K to 10K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
83K to 276K🎙 Daily cadence·195 episodes·Last published today - Monthly Reach
Unique listeners across all episodes (30 days)
277K to 921K🇵🇪33%🇰🇷11%🇸🇪11%+22 more - Active Followers
Loyal subscribers who consistently listen
111K to 368K
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
—
Total Plays
—
Total Reviews
—
* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
On the show
From 10 epsHosts
Recent guests
Recent episodes
241: Foundation Models in Pathology: Strong on Paper, Ready for Labs?
Jun 24, 2026
42m 07s
240: AI-Powered Companion Diagnostics: The Future of Precision Medicine | Podcast with Dr Bowman
Jun 17, 2026
41m 05s
239: Can AI Copilots Keep Up with Pathologists?
Jun 3, 2026
33m 25s
238: How Do We Know AI Is Ready for Pathology
May 19, 2026
19m 58s
237: Why Pathology Vendor's Don't Speak the Same Language?
May 18, 2026
33m 08s
Social Links & Contact
Official channels & resources
Official Website
Login
RSS Feed
Login
| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 6/24/26 | 241: Foundation Models in Pathology: Strong on Paper, Ready for Labs? | Send us Fan Mail Are pathology foundation models actually ready for labs, or are they still stronger on paper than in practice? In this episode of DigiPath Digest #49, I unpack a timely review on pathology foundation models and ask the question that matters most to me: not just what these models can do, but what has to be true before they are genuinely useful in real pathology workflows. I walk through how pathology AI moved from narrow, task-specific models into the era of transformer-based ... | 42m 07s | ||||||
| 6/17/26 | 240: AI-Powered Companion Diagnostics: The Future of Precision Medicine | Podcast with Dr Bowman | Send us Fan Mail How far can pathologists take visual biomarker scoring before human vision becomes the bottleneck? In this episode, I talk with Doug Bowman. PhD, VP Precision Medicine at Indica Labs, about what happens when companion diagnostics move from traditional visual scoring into the era of AI-powered image analysis. Doug comes from a biomedical and electrical engineering background, with experience in microscopy, digital image analysis, pharma workflows, and now precision medicine at... | 41m 05s | ||||||
| 6/3/26 | 239: Can AI Copilots Keep Up with Pathologists?✨ | AI in pathologydigital pathology+3 | — | DALPHIN: Benchmarking Digital Pathology AI Copilots Against Pathologists on an Open Multicentric Dataset | — | AI copilotsdigital pathology+3 | — | 33m 25s | |
| 5/19/26 | 238: How Do We Know AI Is Ready for Pathology✨ | digital pathologyAI in healthcare+3 | — | Leica | Berlin | digital pathologyAI+3 | — | 19m 58s | |
| 5/18/26 | 237: Why Pathology Vendor's Don't Speak the Same Language?✨ | digital pathologyinteroperability+3 | — | DICOMDigiPath Digest | — | digital pathologyinteroperability+4 | — | 33m 08s | |
| 5/15/26 | 236: What Happens When a Patient Sees Their Cancer for the First Time | Podcast with Michele Mitchell✨ | cancerpatient experience+3 | Michele Mitchell | Michigan MedicineASCP+2 | — | cancerpathology report+3 | — | 1h 12m 49s | |
| 5/12/26 | 235: From Cytology to Omics: Where Pathology AI Gets Harder✨ | AI in pathologycomputational pathology+4 | — | AIcomputational pathology+5 | — | AIpathology+5 | — | 32m 49s | |
| 4/25/26 | 234: Quality, Teaching, and AI: A Practical Shift in Pathology✨ | AI in pathologydigital pathology+4 | — | PubMedAI+6 | — | digital pathologyAI+5 | — | 35m 51s | |
| 4/24/26 |  233: AI-Driven Breast Cancer Staging in Resource-Constrained Settings✨ | AI in healthcarebreast cancer staging+3 | — | Journal of Pathology InformaticsDeep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings | — | AIbreast cancer+4 | — | 21m 25s | |
| 4/22/26 |  232: AI and Digital Pathology in Case-Based Renal Education✨ | AI in healthcaredigital pathology+3 | — | Clin TeachIntegrating AI-Powered Digital Pathology With Case-Based Teaching: A Novel Paradigm for Renal Education in Medical School | — | AIdigital pathology+4 | — | 18m 04s | |
Want analysis for the episodes below?Free for Pro Submit a request, we'll have your selected episodes analyzed within an hour. Free, at no cost to you, for Pro users. | |||||||||
| 4/20/26 |  231: The Future of Bone Marrow Biopsy: Omics and AI Integration✨ | bone marrow biopsyomics+4 | — | Front. Med.Advancements in bone marrow biopsy: the role of omics and artificial intelligence in hematologic diagnostics | — | bone marrow biopsyomics+4 | — | 20m 47s | |
| 4/20/26 |  230: Artificial Intelligence in Clinical Oncology: Multimodal Integration and Translational Development✨ | Artificial IntelligenceClinical Oncology+3 | — | Cancer LettersArtificial intelligence in clinical oncology: Multimodal integration and translational development | — | Artificial IntelligenceClinical Oncology+5 | — | 20m 51s | |
| 4/20/26 |  229: Spatial Omics and AI for Clinically Actionable Cancer Biomarkers | Send us Fan Mail Paper Discussed in this Episode: Spatial omics and AI for clinically actionable cancer biomarkers. Reitsam NG. PLoS Med 2026; 23(4): e1005049. Episode Summary: In this deep dive, we explore how artificial intelligence and spatial omics are fundamentally rewriting the rules of cancer diagnostics. We break down a 2026 editorial that challenges a deceptively simple question driving modern oncology: Is a tumor "positive" or "negative" for a biomarker? As targeted cancer therapies... | 22m 37s | ||||||
| 4/11/26 | 228: GPT-5 and Gemini 2.5 Pro read pathology slides - here is how they did… | Send us Fan Mail I did something I've never done before for this episode — I went live from the middle of a national park. This is DigiPath Digest #42, broadcasting from the Great Sand Dunes National Park in Colorado via Starlink from my family road trip. Yes, it actually worked. And so did the papers. This episode covers four papers that all ask the same uncomfortable question from different angles: how close is AI to being genuinely useful in real pathology practice — and what's still stand... | 24m 15s | ||||||
| 4/10/26 |  227: Implementing Generative AI and LLM Assistants in Oncology Practice | Send us Fan Mail Paper Discussed in this Episode: How to bring generative AI to oncology practice. D. Truhn & J. N. Kather. ESMO Real World Data and Digital Oncology 2026. Episode Summary: In this journal club deep dive, we step out of the theoretical sci-fi hype of artificial intelligence and look at a practical, real-world roadmap for bringing Generative AI into oncology. We examine a 2026 paper that maps out the trajectory for deploying Large Language Models (LLMs) to combat the overwh... | 24m 19s | ||||||
| 4/10/26 |  226: LLM Performance in Cervical Cytology Interpretation: GPT-5 vs. Gemini 2.5 | Send us Fan Mail Paper Discussed in this Episode: Can large language models like ChatGPT and Gemini interpret cervical cytology accurately? Saroja Devi Geetha. Annals of Diagnostic Pathology 2026; Volume 83, 152641. Episode Summary: In this journal club deep dive, we explore what happens when advanced artificial intelligence is thrown into the visually chaotic realm of human biology. We examine a 2026 study evaluating whether two massive multimodal models—GPT-5 and Gemini 2.5 Pro—can accurate... | 24m 50s | ||||||
| 4/10/26 |  225: Artificial Intelligence in Oral Oncology: Diagnosis and Therapeutic Integration | Send us Fan Mail Paper Discussed in this Episode: Artificial intelligence in oral oncology: Current advances and future potential in diagnosis, prognosis, and therapeutic decision-making. Annamalai A, Dhanes V, Jayalakshmi L, Shanmugam R, Ravi S. Cancer Treatment and Research Communications 47 (2026) 101193. Episode Summary: In this journal club deep dive, we explore how AI is fundamentally reshaping the clinical management of Oral Squamous Cell Carcinoma (OSCC). We examine a comprehensive Ma... | 13m 45s | ||||||
| 4/10/26 |  224: AI and Computational Pathology in Breast Cancer Care | Send us Fan Mail Paper Discussed in this Episode: How artificial intelligence applied to digital pathology could guide treatment personalization in breast cancer. T. Ruelle, T. Grinda, L. Del Mastro, M. Lacroix-Triki, B. Pistilli & G. Gessain. ESMO Real World Data and Digital Oncology 2026. Episode Summary: In this journal club episode, we step into the reality of computational pathology and explore how artificial intelligence is fundamentally transforming breast cancer diagnostics. We ex... | 25m 40s | ||||||
| 4/8/26 | 223: You Don’t Need a Scanner to Start Digital Pathology | ACVP Podcast | Send us Fan Mail You don't need a fancy scanner, a huge budget, or a computational background to get started in digital pathology. That's what I told the ACVP podcast — and I meant it. In this episode, I share my full digital pathology journey: from being completely intimidated by scanners during residency, to building a career that combines toxicologic pathology, image analysis, and remote work at a global CRO. If you're a resident, a trainee, or even a seasoned pathologist who hasn't fully ... | 15m 55s | ||||||
| 4/6/26 | 222: From Slides to Survival: Can AI Close the Gap? | Send us Fan Mail How close is pathology AI to making decisions that matter in real workflows, real trials, and real patient care? In this episode of DigiPath Digest, I review five recent papers that approach that question from very different angles. We look at multimodal survival prediction in cervical cancer, pathology-driven response assessment in neoadjuvant immunotherapy for head and neck squamous cell carcinoma, AI-assisted Ki-67 scoring in pulmonary neuroendocrine neoplasms, automation ... | 40m 36s | ||||||
| 4/3/26 |  220: UPATHLN: Uncertainty-Aware AI for Pan-Cancer Lymph Node Assessment | Send us Fan Mail Paper Discussed in this Episode: High-Sensitivity Pan-Cancer AI Assessment of Lymph Node Metastasis via Uncertainty Quantification. Wang X, Chen Y, Liu X, et al. npj Digit. Med. (2026). Episode Summary: In this episode, we explore a groundbreaking 2026 study that tackles the "black box" problem of medical AI. We dive into UPATHLN, a pan-cancer AI platform for detecting lymph node metastases that doesn't just try to be right—it explicitly knows when it might be wrong. By using... | 22m 59s | ||||||
| 4/3/26 |  219: POLARIS: Reliable AI Classification and Risk Stratification of Colorectal Polyps | Send us Fan Mail Paper Discussed in this Episode: Reliable classification of polyps based on artificial intelligence: a development and validation study. Julbø FMI, Henriksen AL, et al. eClinicalMedicine 2026;93: 103826. Episode Summary: In this journal club deep dive, we explore a groundbreaking 2026 study that tackles the massive bottleneck in gastrointestinal pathology caused by successful colorectal screening programs. We examine POLARIS, an AI triage system designed to safely clear over ... | 27m 15s | ||||||
| 4/3/26 |  218: AI-Driven Triage for Enhanced Breast Cancer Diagnostic Workflows | Send us Fan Mail Paper Discussed in this Episode: A Deep Learning Framework for Automated Triage of Breast Cancer Biopsies in Malaysia: A Simulation Study to Reduce Resource Consumption and Diagnostic Turnaround Time. Yudi Kurniawan Budi Susilo, Dewi Yuliana, Shamima Abdul Rahman, Siew Lian Leong. Clinical Breast Cancer 2026 . Episode Summary: In this deep dive, we explore a revolutionary approach to a massive real-world healthcare bottleneck: agonizingly long diagnostic wait times in resourc... | 19m 25s | ||||||
| 4/2/26 |  217: AI vs. Pathologist: Validating Ki-67 Assessment in Pulmonary Neuroendocrine Neoplasms | Send us Fan Mail Paper Discussed in this Episode: Ki-67 Proliferation Index in Pulmonary Neuroendocrine Neoplasms: Interobserver Agreement Among Pathologists and Comparison of Two Artificial Intelligence-Based Image Analysis Systems. Teoman G, Turkmen Usta Z, Sagnak Yilmaz Z, Ersoz S. MDPI 2026. Episode Summary: In this journal club deep dive, we step into the lab to examine a direct comparison between expert human pathologists and artificial intelligence. We explore a 2026 study that evaluat... | 15m 05s | ||||||
| 4/2/26 |  216: Multimodal Deep Learning for Predicting Cervical Cancer Survival Outcomes | Send us Fan Mail Deep Learning Can Predict the Overall Survival of Cervical Cancer Based on Histopathological Image, Gene Mutation and Clinical Information. Shen J, Miao Z, Wang L, et al. IET Systems Biology 2026. Episode Summary: In this deep dive, we explore a groundbreaking 2026 study that uses multimodal deep learning to act as a "master diagnostician" for cervical cancer. We examine what happens when an AI is fed a combination of standard clinical data, cutting-edge genetic sequencing, a... | 23m 36s | ||||||
Showing 25 of 241
Pitch Fit is a Pro feature
See how bookable this show is for guests, which brands already advertise, the per-episode ad value, and the best-fit guest and sponsor profile. The numbers are blurred on the free plan.
How readily this show books outside guests like you.
How proven this show is for host-read sponsorships.
For Guests
ProFor Advertisers
ProUpgrade to Pro to unlock guest cadence, sponsor categories, fit scores, and per-episode ad value for this show.
Chart Positions
27 placements across 25 markets.
Chart Positions
27 placements across 25 markets.