Blog.research.google
Multimodal medical AI – Google Research Blog
WEBThe resulting generalist medical AI system is a multimodal version of Med-PaLM that we call Med-PaLM M. The flexible multimodal sequence-to-sequence architecture allows us to interleave various types of multimodal biomedical information in a single interaction. To the best of our knowledge, it is the first demonstration of a single unified
Actived: 6 days ago
URL: https://blog.research.google/2023/08/multimodal-medical-ai.html?linkId=8927847&m=1
Expanding the Application of Deep Learning to Electronic Health …
WEBExpanding the Application of Deep Learning to Electronic Health Records. Tuesday, January 22, 2019. Posted by Alvin Rajkomar, MD and Eyal Oren, PhD, Google AI, Healthcare. In 2018 we published a paper that showed how machine learning, when applied to medical records, can predict what might happen to patients who are hospitalized: for …
Google Research, 2022 & beyond: Health
WEBGoogle’s focus on AI stems from the conviction that this transformational technology will benefit society through its capacity to assist, complement, and empower people in almost every field and sector. In no area is the magnitude of this opportunity greater than in the spheres of healthcare and medicine.Commensurate with our mission …
Enabling large-scale health studies for the research community
WEBPosted by Chintan Ghate, Software Engineer, and Diana Mincu, Research Engineer, Google Research. As consumer technologies like fitness trackers and mobile phones become more widely used for health-related data collection, so does the opportunity to leverage these data pathways to study and advance our understanding of …
Does Your Medical Image Classifier Know What It Doesn’t Know
WEBOur model architecture and the HOD loss. The encoder (green) represents the wide ResNet 101x3 model pre-trained with different representation learning models (ImageNet, BiT, SimCLR, and MICLe; see below).The output of the encoder is sent to the HOD loss where fine-grained and coarse-grained predictions for inliers (blue) and …
Learning from deep learning: a case study of feature discovery and
WEBPosted by Ellery Wulczyn and Yun Liu, Google Research. When a patient is diagnosed with cancer, one of the most important steps is examination of the tumor under a microscope by pathologists to determine the cancer stage and to characterize the tumor. This information is central to understanding clinical prognosis (i.e., likely patient …
AMIE: A research AI system for diagnostic medical reasoning and
WEBAMIE was optimized for diagnostic conversations, asking questions that help to reduce its uncertainty and improve diagnostic accuracy, while also balancing this with other requirements of effective clinical communication, such as empathy, fostering a relationship, and providing information clearly.
Robust and efficient medical imaging with self-supervision
WEBEvaluation and results. To evaluate the REMEDIS model’s performance, we simulate realistic scenarios using retrospective de-identified data across a broad range of medical imaging tasks and modalities, including dermatology, retinal imaging, chest X-ray interpretation, pathology and mammography.We further introduce the notion of data …
Detecting Signs of Disease from External Images of the Eye
WEBPosted by Boris Babenko, Software Engineer and Naama Hammel, Clinical Research Scientist, Google Health. Three years ago we wrote about our work on predicting a number of cardiovascular risk factors from fundus photos (i.e., photos of the back of the eye) 1 using deep learning.That such risk factors could be extracted from fundus photos …
Multi-task Prediction of Organ Dysfunction in ICUs
WEBPosted by Subhrajit Roy, Research Scientist and Diana Mincu, Research Software Engineer, Google Research. The intensive care unit (ICU) of a hospital looks after the most medically vulnerable patients, many of whom require organ support, such as mechanical ventilation or dialysis.While always critical, the demand on ICU services …
Responsible AI at Google Research: Context in AI Research (CAIR)
WEBThe CAIR team is committed to creating opportunities to hear more perspectives in AI development. We partnered with Sisonkebiotik to co-organize the Data Science for Health Workshop at Deep Learning Indaba 2023 in Ghana. Everyone’s voice is crucial to developing a better future using AI technology.
An International Scientific Challenge for the Diagnosis and Gleason
WEBDesign of the Panda Challenge. The challenge had two phases: a development phase (i.e., the Kaggle competition) and a validation phase. During the competition, 1,290 developers from 65 countries competed in building the best performing Gleason grading algorithm, having full access to a development set for algorithm training.
Google Research, 2022 & beyond: Natural sciences
WEBIn 2022 we celebrated the remarkable achievements of the Telomere-2-Telomere (T2T) Consortium in resolving these previously unavailable regions — including five full chromosome arms and nearly 200 million base pairs of novel DNA sequences — which are interesting and important for questions of human biology, evolution, and disease.
Google Research Blog
WEBPosted by Lizao (Larry) Li, Software Engineer, and Rob Carver, Research Scientist, Google Research. Accurate weather forecasts can have a direct impact on people’s lives, from helping make routine decisions, like what to pack for a day’s activities, to informing urgent actions, for example, protecting people in the face of hazardous weather conditions.
Self-Supervised Learning Advances Medical Image Classification
WEBCombining these self-supervised learning strategies, we show that even in a highly competitive production setting we can achieve a sizable gain of 6.7% in top-1 accuracy on dermatology skin condition classification and an improvement of 1.1% in mean AUC on chest X-ray classification, outperforming strong supervised baselines pre …
SCIN: A new resource for representative dermatology images
WEBThe Fitzpatrick Skin Type scale was originally developed as a photo-typing scale to measure the response of skin types to UV radiation, and it is widely used in dermatology research. The Monk Skin Tone scale is a newer 10-shade scale that measures skin tone rather than skin phototype, capturing more nuanced differences between the darker skin …
Google at CHI 2023 – Google Research Blog
WEBPosted by Malaya Jules, Program Manager, Google. This week, the Conference on Human Factors in Computing Systems (CHI 2023) is being held in Hamburg, Germany. We are proud to be a Hero Sponsor of CHI 2023, a premier conference on human-computer interaction, where Google researchers contribute at all levels. This …
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