Medical Device Developments的动态

Big news in the world of artificial intelligence, innovation and cancer detection – Hologic, Inc.’s Genius Digital Diagnostics System with the Genius Cervical AI algorithm has received clearance from the FDA.?This is a potential game changer for our laboratory partners, helping to alleviate the shortage of laboratory professionals, improving workflow and efficiency.?By allowing cytologists and pathologists to securely review cases remotely, patients, particularly those in medically underserved areas, can benefit from the collective knowledge of geographically dispersed experts. The ultimate goal??Expanding access to the most comprehensive cervical cancer screening available and eradicating this preventable disease. https://ow.ly/8cAY50Qx0iv #cervicalcancer #healthcareinnovation #womenshealth

May is #SkinCancerAwareness month, and at BioAI, we are on a mission to identify more efficacious treatments for skin cancer patients. In this past webinar, Bio-AI Health in collaboration with Dr. Paolo Ascierto and his clinical laboratory at the National Tumor Institute “Fondazione G. Pascale” in Naples, Italy demonstrated how AI and Deep learning were used on H&E samples to predict the BRAF molecular status of patients as well as for the prediction of immunotherapy. https://lnkd.in/gTXQuDGT

Current mood: AI Capable of Detecting Breast Cancer Up to 5 Years in Advance Recently, scientists at MIT have developed a new artificial intelligence (AI) capable of detecting breast cancer up to five years before clinical diagnosis. This innovation could transform early intervention and save countless lives. The AI model analyzed chromatin images obtained from 560 tissue samples of 122 patients, identifying eight distinct cellular states in various stages of ductal carcinoma in situ (DCIS). Unlike traditional techniques, this model considers not only the cellular composition but also their spatial arrangement, revealing that tissue organization is crucial for predicting cancer progression. Surprisingly, the model can identify cellular states associated with invasive cancer even in tissues that appear normal to the human eye. Its simplicity and interpretability make it a valuable tool for radiologists, improving diagnostic accuracy and potentially influencing the frequency of mammograms. Current five-year survival rates for breast cancer are around 90% if detected early. The ability to anticipate the diagnosis by five years could significantly improve patient outcomes. This discovery is just the beginning. In the coming years, AI could revolutionize early diagnosis, personalized treatments, and the discovery of new drugs. As we continue to harness the power of AI, we are not only improving healthcare but also opening new pathways for disease prevention and treatment. Source: https://lnkd.in/e9xF5YmV?? Radiological Society of North America (RSNA) ???? [email protected]

Tuesday Lunch Break News Update: Another AI product approval this week. Hologic, Inc. has won an FDA clearance for its AI-enabled cervical cancer screening system. "The product, the Genius Digital Diagnostics System, creates digital images of Pap test slides and uses an AI algorithm to identify cells that cytologists and pathologists should review." "According to Hologic, a study linked the technology to a “28% reduction in false negatives of high-grade squamous intraepithelial and more severe lesions compared to microscopic review.” The reduction in false negatives could translate into the detection of more cancers." 28% reduction? Wow. AI diagnosis isn't going away. Clinical decision support is here to stay. #medtech #AI #clinicaldecisionsupport https://lnkd.in/evBiS4HW

AI path news.Sep 09, 2024. Roche advances AI-driven cancer diagnostics by expanding its digital pathology open environment. The Roche Digital Pathology Open Environment brings together a wide array of innovative AI-based pathology tools to help clinicians improve patient care and expand personalised healthcare. Roche is now integrating more than 20 artificial intelligence (AI) algorithms from eight new collaborators into its digital pathology open environment. Roche collaborators are: - Deep Bio: Algorithm for prostate cancer detection, grading, and tumour quantification - DiaDeep: Algorithms for breast cancer biomarker quantification - Lunit: Tumour proportion score (TPS) analysis for non-small cell lung cancer - Mindpeak: Algorithms for breast biomarkers and pan tumour PD-L1 for lung, gastric, esophageal, bladder and breast cancers - Owkin: Algorithm for the screening of microsatellite stability in colorectal cancer - Qritive: Algorithms for screening and grading of prostate cancer, analysing lymph nodes for metastasis, and screening for colon cancer - Sonrai Analytics: Algorithm for determining microsatellite instability (MSI) status in colorectal cancer - Stratipath: Algorithm for risk profiling of invasive breast cancer. ... https://lnkd.in/ddExGxKt #AI #pathology #roche

Fantastic breakthrough For women who worry about breast cancer ??MIT researchers have developed an AI model capable of detecting breast cancer up to 5 years before clinical diagnosis, potentially revolutionising early intervention and saving countless lives. Here's a breakdown of this groundbreaking technology: ?The AI analysed chromatin images from 560 tissue samples across 122 patients, identifying 8 distinct cell states throughout various stages of ductal carcinoma in situ (DCIS). ?The model considers both cellular composition and spatial arrangement, revealing that tissue organization is crucial in predicting disease progression. ?Utilising a convolutional variational autoencoder, the AI learns from simple chromatin staining images - a more cost-effective and accessible method compared to complex sequencing techniques. ?Remarkably, the model detected cell states associated with invasive cancer even in tissue that appeared normal to the human eye. With current 5-year survival rates for breast cancer at approximately 90% when detected early, this 5-year head start on diagnosis and treatment could significantly improve patient outcomes. However, this breakthrough is just the tip of the iceberg. The potential impact of AI on healthcare in the coming decade is likely to surpass most expectations. From early disease detection to personalized treatment plans and drug discovery, AI is poised to transform medical practice and patient care in ways we're only beginning to imagine. As we continue to harness the power of AI in medicine, we're not just improving healthcare - we're redefining what's possible in our fight against diseases like cancer.

Have you read the latest from Ted M. Diehl, CMR, and Wayne Brinster?

Digital Clinics Research and Services Pvt Ltd #digiclinics In CancerCare, early clinical intervention can be the difference between life and death. Treatement decision-making in Breast Cancer (BC) is complex, involving the assessment of a myriad of factors, especially, Pathological Analysis/Grading, which is Gold Standard for Breast Cancer Diagnosis. #digitalclinics, provides totally automated CAP, RSNA imaging diagnostic workflows using AI driven imaging markers detection pipelines for Nottingham Cancer Grading, BI-RADS Screening Scores and BC Sub-typing. Our Streamlined diagnostic processes empower clinical care teams to make informed decisions, with greater insights on disease pathogenisis process through AI algorithms, which are assisting pathologists whether discernible to the human eye or not, enables a more accurate and expedited diagnosis. #digitalclinics' Value Proposition To EndCusotmers - Patients: Facilitating Faster, Crucial, Precise Treatment pathways to enhance the chances of survival To Enterprises - Hospitals, Diag Centers:? ?Clinician designed, validated system for Clinicians, enabling them to focus much higher clinical tasks? ?Reduce lab Cost & Time, Improving Pathologists/Radiologists Efficiency & Productivity ?Multi-millions Long Term Revenue Potential (Enterprise-to-Enterprise) – “1. Cancer Hospitals, Cancer Diagnostics Centre Lab Automation, ?2. Value Add Diag Services combined, Med Device OEM’s Device+Diag SW” https://lnkd.in/gbCTAU-c

Deep Bio Inc., a leader in AI-powered cancer diagnostics has announced its collaboration with Roche to integrate its advanced suite of AI algorithms into the navify? Digital Pathology platform. This collaboration aims to enhance digital pathology capabilities, offering a comprehensive menu of AI solutions, starting with DeepDx Prostate, a clinically validated algorithm for prostate cancer analysis. Deep Bio’s algorithms provide pathologists with precise and efficient diagnostic tools that enhance accuracy in cancer detection, grading, and tumor quantification. The seamless integration into existing pathology workflows will leverage AI to unlock new insights and data, driving better treatment decisions. DeepDx Prostate has undergone extensive testing, analyzing over 700,000 core needle biopsies in the U.S., marking it as one of the most thoroughly vetted solutions in its field. This advanced algorithm offers pathologists accurate AI-enabled prostate cancer diagnosis, gland-level Gleason grading, and tissue and tumor measurements, all within the navify??Digital Pathology workflows. Deep Bio’s DeepDx Prostate is CE Marked and has been validated through comprehensive clinical studies published in peer-reviewed journals. With distinctions such as the Silver Edison Award and the CES Innovation Award, Deep Bio is dedicated to pioneering innovative technologies to enhance clinical outcomes. To read this article in full, read the press release in full on Pathology News... ?? https://lnkd.in/e3GhV3GR #pathologynews #digitalpathology

This paper discusses the transformative impact of AI on breast cancer diagnosis and management, highlighting its potential benefits and challenges. 1?? AI integration in breast cancer management promises significant advancements in detection, diagnosis, and treatment. 2?? Given breast cancer's prevalence and impact, innovative approaches like AI are crucial to improving patient outcomes. 3?? AI excels in analyzing extensive medical datasets and detecting subtle patterns, providing accurate predictions across all stages of breast cancer management. 4?? AI's capability to analyze mammograms and other medical images enhances early detection, identifying abnormalities that might escape human perception. 5?? Issues like false positives in AI-assisted detection systems and the need for high-quality training datasets for deep learning models must be addressed. 6?? The variability and operator dependence of ultrasound images present unique challenges that need to be overcome. 7?? AI-driven personalized treatment strategies, based on genetic and molecular data, tailor therapies to individual patients, optimizing effectiveness and minimizing adverse effects. 8?? AI guides radiotherapy planning, optimizing treatment effectiveness while reducing planning time and variability between different treatment planners.