Proactive’s Post

🔬 Revolutionizing Tumor Detection with Hyperspectral Imaging (HSI) HSI is an emerging non-invasive technology offering precise solid tumor detection. By capturing detailed spatial and spectral information, it identifies cancerous tissues through their unique spectral "fingerprints." This advanced imaging method enables real-time, label-free assistance during surgeries, enhancing both detection and diagnosis accuracy. HSI is paving the way for earlier cancer detection, improved surgical outcomes, and a future where medical imaging becomes even more powerful. Read more: https://lnkd.in/gGg2JQXf #HyperspectralImaging #MedicalInnovation #CancerDetection #SolidTumors #ImagingTechnology #HealthcareInnovation

Read about how Perimeter Medical Imaging AI is using AI to help surgeons remove all breast cancerous cells on the first surgery. #AI #healthcareinnovations

New published paper! This peer-reviewed study highlights the potential for #AI and wide-field (WF) OCT in breast cancer surgery to enhance productivity and decision making in surgical margin assessment, decreasing reoperation rates due to residual cancer. The results suggest the investigational* deep learning model accurately identified 96.8% of pathology positive margins in WF-OCT images with high sensitivity and specificity. Read it at https://lnkd.in/dmxWFTCM. #artificialintelligence #AI #deeplearning #healthcareinnovation #breastcancer -- *CAUTION. Investigational Device. Subject to U.S. Law. Not available for sale in the United States.

Our peer-reviewed publication on the novel use of wide-field OCT and AI as a one-two combo punch to tackle breast cancer surgical oncology margins is out! You can read the details in the paper but the key statistics is 97% pathology positive margin identification while achieving 93% sensitivity and 98% specificity. Compare this number to the published results revealing 21.1% and 14.9% reoperation rates among commercially insured patients and the Medicare cohort (bit.ly/3wwMkp1). Many thanks to my co-authors Yanir Levy, David Rempel, Mark Nguyen, Ali Yassine, Maggie Sanati-Burns, Dr Payal Salgia, Bryant Lim, Sarah Butler, PhD, and Andrew Berkeley. Perimeter Medical Imaging AI, #AI, #OCT #breastcancer #margin #oncology #surgical

Comparison of dosimetry with magnetic resonance and computed tomography imaging delineation of surgical bed volume in breast cancer irradiation Recent #research published in #CancerPathogenesisandTherapy examines the potential benefits of using #MagneticResonanceImaging and #ComputedTomography as pre-treatment #imaging modalities to #boost dosimetry. Read more: https://lnkd.in/gjPZSudx

How is AI transforming breast cancer detection while addressing radiologist burnout? This article explores groundbreaking developments in AI-assisted mammography that could reshape approaches to early diagnosis and personalized screening. What are your thoughts on the role of AI in the future of healthcare? https://bit.ly/3WfLirX

AI in Clinical Trials? This review pasted below concluded while the future is bright, the road is bumpy. Most current applications in trials are for patients recruitment. I saw a little bit more AI in clinical practice, or in other words, patient care in a patient-centric era, often the practice will be linked to future trials. A few examples I was involved: 1. Lung Cancer surgery AI guided CT-imaging 3D reconstruction. This AI tool helps to reduce surgical time from >140min to ~120min. Result was published on Lancet eBioMed. As this tool was already applied in major hospitals, you may soon see a slightly different early Lung Cancer patient population for your study. 2. Lung Cancer surgery recovery: an AI tool/environment was developed to guide patients how to exercise after surgery. It reduces the “recovery time“. It’s a fun cellphone app, patients just loved it. A phase I trial is done (I am proud to be a designer). 3. Can AI help CRC/CRA to reduce their workload and still ensure the quality of trial data entry? We examined the AI/human combo vs CRC/CRA pair, and found it’s possible. Result will be presented this month in a major conference. There are other applications as well. As the AI era is approaching, we need to embrace it, even in the heavily regulated clinical trials.

I believe the more valuable job that AI can support clinical trials is to provide suggestions to the decision-maker by calculating the ratio of success for different development strategies.

Great article below ⬇️ reviewing the positive impact of breast AI for radiologists.

👉🏼 RARPKB: A knowledge-guide decision support platform for personalized robot-assisted surgery in prostate cancer 🤓 Jiakun Li 👇🏻 https://lnkd.in/ek3grU9g 🔍 Focus on data insights: - The platform comprised 583 studies, 1589 cohorts, 1,911,968 patients, and 11,986 records, resulting in 54,834 data entries. - Knowledge-guided decision support tool provides personalized surgical plan recommendations and potential complications based on patients' baseline and surgical information. - RARPKB outperformed ChatGPT-4 in authenticity, matching, personalized recommendations, matching of patients, and personalized recommendations for complications. 💡 Main outcomes and implications: - Introduction of RARPKB, the first knowledge base for robot-assisted surgery with a focus on prostate cancer. - Assistance in personalized and complex surgical planning for prostate cancer to enhance efficacy. - Reference for future applications of artificial intelligence in clinical practice. 📚 Field significance: - Advancement in personalized treatment plans for robot-assisted surgery in prostate cancer. - Integration of data insights to improve decision-making in surgical interventions. - Potential for enhancing the role of artificial intelligence in clinical practice. 🗄️: [#prostate cancer, #robot-assisted surgery, #data insights, #surgical planning, #artificial intelligence]