Embie Clinic’s Post

What I read this week.. - Researchers at Meta published a paper proposing "Generative Recommenders (GRs)", a new paradigm for large-scale recommendation systems that formulates ranking and retrieval tasks as sequential transduction problems. The approach shows promising gains and better scaling - Lancet report on fertility rates predicts that two-thirds of the countries will be below replacement level by 2050 Substack: https://lnkd.in/ewxaH2xm #AI #RecommendationSystems #ML #Lancet

📢 #HighlyCited 1. Low-Resource Neural Machine Translation Improvement Using Source-Side Monolingual Data https://lnkd.in/dAtk6kpt 2. Hyperparameter Optimization of Ensemble Models for Spam Email Detection https://lnkd.in/geVAVJ7K 3. Crop Disease Diagnosis with Deep Learning-Based Image Captioning and Object Detection https://lnkd.in/gd52Bu8r 4. Ghost-ResNeXt: An Effective Deep Learning Based on Mature and Immature WBC Classification https://lnkd.in/gDD73fqu

New in our blog: We look at a paper that suggests that, when applied to exome sequencing data, a type of #AI called machine learning may let scientists understand how copy number variants contribute to neurodevelopmental disorders. https://buff.ly/3MSBT4i

Join us for Datamatics' 'Thoughtful Thursday' as we explore the game-changing impact of Gen AI in healthcare, particularly in pathology reports! 🩺 Discover how TruCap+ GenAI uses NLP algorithms to extract key insights, aiding in report summarization and precise inquiries. Exciting, right? But integrating Gen AI into practice requires careful consideration of privacy and ethics. Let's dive in deeper! Click the link to join the conversation. 💬 https://lnkd.in/drHRxUA9 Blessy Varghese #genai #healthcareinnovation #pathology #thoughtfulthursday

ᴏɴᴇ ᴍᴏʀᴇ ᴘᴀᴛᴇɴᴛ ɢᴏᴛ ❈✶ 🎀 "ɢʀᴀɴᴛ" ❈✶ 🎀  ꜱᴛᴀᴛᴜꜱ, ʜᴀᴘᴘʏ ᴛᴏ ꜱʜᴀʀᴇ ᴛʜɪꜱ. This is in the area of Deep Learning, especially "Image Classification" https://lnkd.in/gP3X7jub #cnn #imageprocessing #deeplearning #machinelearning #computervision #ai #genai #llm Generally, conventional mechanisms for diagnosing diseases using image classifications are costly, time consuming, and inaccurate. In many cases, such conventional mechanisms may require precautions to be taken for specific diagnosis. For example, conventional mechanisms may require human intervention with manual validation steps. Further, conventional mechanisms are computationally intensive and may require significant storage and processing power....... c̲o̲n̲t̲i̲n̲u̲e̲d̲ ̲i̲n̲ ̲t̲h̲e̲ ̲a̲t̲t̲a̲c̲h̲e̲d̲ ̲l̲i̲n̲k̲ Patent number: 11822624 Type: Grant Filed: Mar 5, 2021 Date of Patent: Nov 21, 2023 Patent Publication Number: 20220207306

Excited to share our research paper published with IEEE: "Web Application to Predict Skin Disease: An Approach Using Deep Learning Algorithm." This innovative system leverages advanced machine learning techniques for early detection of skin diseases, significantly enhancing diagnostic accuracy and patient care. Ayingaran Arumugavel Sharujan Ganeshan Makenthiran Dalaxshan #DeepLearning #HealthcareInnovation #SkinDisease #MachineLearning #AI

Save time in your day with Argus so that you spend more time caring for your next patient. Argus® NLP allows you to document the report exactly as desired with details that cannot always be found in a dropdown menu. Any aspect of the report created in Argus® can be searched and reported using talk-to-free text. Learn more about Argus at www.argusml.com #AI #pathology #GI #report #workflow #healthit #artificialintelligence #software #biopsy #Gastr

Disentangled latent variables in the hippocampus Ok, that is my short summary interpretation (for AI nerds) of an intriguing article by a Cedars-Sinai-led team. From the abstract: "Here we characterized the representational geometry of populations of neurons (single units) recorded in the hippocampus, amygdala, medial frontal cortex and ventral temporal cortex of neurosurgical patients performing an inferential reasoning task. We found that only the neural representations formed in the hippocampus simultaneously encode several task variables in an abstract, or disentangled, format. This representational geometry is uniquely observed after patients learn to perform inference, and consists of disentangled directly observable and discovered latent task variables." Translation: the researchers recorded individual neurons in multiple brain areas (in patient volunteers undergoing surgical treatment for epilepsy) and were able to show that only in the hippocampus did neuronal activation patterns represent the same concept in different contexts, such as relationships between items. One canonical AI example from the early days of word2vec would be the ability to recognize king:man/queen:woman as a single concept. Another intriguing result: participants who did not initially recognize a concept but were then told about it had their hippocampal neuronal activation patterns reconfigured quickly to accommodate the new insight -with one "example". Rapid learning of the concept lead to the same abstract representations as slow learning from examples. See also https://lnkd.in/g5nSS8C9 for a nice perspective on the paper. https://lnkd.in/g-bZM7Rw

A vital fireside chat on how to integrate patient-centered innovation to accelerate therapeutic development with Michael Fronstin and Christopher P. Boone, from Oracle Life Sciences. Great learnings on integrating patient-centered research and data that highlights the impact of connecting genomic and real-world data with generative AI. #REpharmaUSA

Future-proof your clinical genomics reporting, data integration, analytics, and clinical care pathways with GenomOncology! Watch our on-demand webinar today and learn more about: ✔️ The robust features and capabilities of GenomOncology's precision oncology software solutions ✔️ How GenomOncology leverages technologies like NLP, OCR, and pre-built applications to ingest, harmonize, and structure unstructured data ✔️ How independent labs and diagnostic providers can elevate their reporting with the autonomous utilization of the GO knowledge base through automated API workflows ✔️ GenomOncology's advancements in AI Watch here: https://lnkd.in/eVHzaP47 #PrecisionOncology #DataEnablement #DataAnalysis