Google Health रिसर्च पब्लिकेशन

अपने काम को प्रकाशित करके, हम हेल्थकेयर में सुधार करने के लिए कई तरह के विचार शेयर कर पाते हैं और सबके साथ मिलकर काम कर पाते हैं. यहां हमारे पब्लिकेशन और काम के ब्लॉग पोस्ट देखें.

सामान्य

क्रॉस-स्पेशलिटी अप्लाइड एआई (AI)

  • ब्लॉग पोस्ट

    How Underspecification Presents Challenges for Machine Learning

    by Alex D’Amour and Katherine Heller

    Google AI Blog | 18-Oct-2021

  • ब्लॉग पोस्ट

    Self-Supervised Learning Advances Medical Image Classification

    by Shekoofeh Azizi

    Google AI Blog | 13-Oct-2021

  • पब्लिकेशन

    Iterative Quality Control Strategies for Expert Medical Image Labeling

    Freeman, B., Hammel, N., Phene, S., Huang, A., Ackermann, R., Kanzheleva, O., Hutson, M., Taggart, C., Duong, Q. & Sayres, R.

    HCOMP 9, 60–71 (2021).

  • पब्लिकेशन

    Big Self-Supervised Models Advance Medical Image Classification

    Azizi, S., Mustafa, B., Ryan, F., Beaver, Z., Freyberg, J., Deaton, J., Loh, A., Karthikesalingam, A., Kornblith, S., Chen, T., Natarajan, V. & Norouzi, M.

    Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) 3478–3488 (2021).

  • पब्लिकेशन

    Privacy-first health research with federated learning

    Sadilek, A., Liu, L., Nguyen, D., Kamruzzaman, M., Serghiou, S., Rader, B., Ingerman, A., Mellem, S., Kairouz, P., Nsoesie, E. O., MacFarlane, J., Vullikanti, A., Marathe, M., Eastham, P., Brownstein, J. S., Arcas, B. A. Y., Howell, M. D. & Hernandez, J.

    NPJ Digit Med 4, 132 (2021).

  • पब्लिकेशन

    Supervised Transfer Learning at Scale for Medical Imaging

    Mustafa, B., Loh, A., Freyberg, J., MacWilliams, P., Karthikesalingam, A., Houlsby, N. & Natarajan, V.

    arXiv [cs.CV] (2021).

  • पब्लिकेशन

    Big Self-Supervised Models Advance Medical Image Classification

    Azizi, S., Mustafa, B., Ryan, F., Beaver, Z., Freyberg, J., Deaton, J., Loh, A., Karthikesalingam, A., Kornblith, S., Chen, T., Natarajan, V. & Norouzi, M.

    arXiv [eess.IV] (2021).

  • पब्लिकेशन

    Underspecification Presents Challenges for Credibility in Modern Machine Learning

    D’Amour, A., Heller, K., Moldovan, D., Adlam, B., Alipanahi, B., Beutel, A., Chen, C., Deaton, J., Eisenstein, J., Hoffman, M. D., Hormozdiari, F., Houlsby, N., Hou, S., Jerfel, G., Karthikesalingam, A., Lucic, M., Ma, Y., McLean, C., Mincu, D., Mitani, A., Montanari, A., Nado, Z., Natarajan, V., Nielson, C., Osborne, T. F., Raman, R., Ramasamy, K., Sayres, R., Schrouff, J., Seneviratne, M., Sequeira, S., Suresh, H., Veitch, V., Vladymyrov, M., Wang, X., Webster, K., Yadlowsky, S., Yun, T., Zhai, X. & Sculley, D.

    arXiv [cs.LG] (2020).

  • पब्लिकेशन

    Contrastive Training for Improved Out-of-Distribution Detection

    जिम विंकेंस, रूडी बुनेल, अभिजीत गुहा रॉय, रॉबर्ट स्टैनफोर्थ, विवेक नटराजन, जोसेफ़ आर॰ लेस्साम, पैट्रिशिया मैकविलियम्स, पुष्मीत कोहली, एलन कार्तिकेसलिंगम, सिमोन कोल, टायलाम सेमजिल, एस॰ एम॰ अली इस्लामी, और ओलफ़ रॉनबर्गर

    arXiv [cs.LG] (2020).

  • पब्लिकेशन

    Customization scenarios for de-identification of clinical notes

    Hartman, T., Howell, M., Dean, J., Hoory, S., Slyper, R., Laish, I., Gilon, O, Vainstein, D., Corrado, G., Chou, K., Po, M., Williams, J., Ellis, S., Bee, G., Hassidim, A., Amira, R., Beryozkin, G., Szpektor, I., & Matias, Y.

    BMC (2020).

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महामारी से संबंधित पूर्वानुमान

  • ब्लॉग पोस्ट

    An ML-Based Framework for COVID-19 Epidemiology

    by Joel Shor & Sercan Arik

    Google AI Blog | 13-Oct-2021

  • ब्लॉग पोस्ट

    Google Cloud, Harvard Global Health Institute release improved COVID-19 Public Forecasts, share lessons learned

    by Tomas Pfister

    Google Cloud Blog | 15-Nov-2020

  • ब्लॉग पोस्ट

    Google Cloud AI and Harvard Global Health Institute Collaborate on new COVID-19 forecasting model

    by Dario Sava

    Google Cloud Blog | 3-Aug-2020

  • पब्लिकेशन

    Algorithmic fairness in pandemic forecasting: lessons from COVID-19

    Tsai, T. C., Arik, S., Jacobson, B. H., Yoon, J., Yoder, N., Sava, D., Mitchell, M., Graham, G. & Pfister, T.

    NPJ Digit Med 5, 59 (2022).

  • पब्लिकेशन

    Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

    Cramer, E. Y., Ray, E. L., Lopez, V. K., Bracher, J., Brennen, A., Castro Rivadeneira, A. J., Gerding, A., Gneiting, T., House, K. H., Huang, Y., Jayawardena, D., Kanji, A. H., Khandelwal, A., Le, K., Mühlemann, A., Niemi, J., Shah, A., Stark, A., Wang, Y., Wattanachit, N., Zorn, M. W., Gu, Y., Jain, S., Bannur, N., Deva, A., Kulkarni, M., Merugu, S., Raval, A., Shingi, S., Tiwari, A., White, J., Abernethy, N. F., Woody, S., Dahan, M., Fox, S., Gaither, K., Lachmann, M., Meyers, L. A., Scott, J. G., Tec, M., Srivastava, A., George, G. E., Cegan, J. C., Dettwiller, I. D., England, W. P., Farthing, M. W., Hunter, R. H., Lafferty, B., Linkov, I., Mayo, M. L., Parno, M. D., Rowland, M. A., Trump, B. D., Zhang-James, Y., Chen, S., Faraone, S. V., Hess, J., Morley, C. P., Salekin, A., Wang, D., Corsetti, S. M., Baer, T. M., Eisenberg, M. C., Falb, K., Huang, Y., Martin, E. T., McCauley, E., Myers, R. L., Schwarz, T., Sheldon, D., Gibson, G. C., Yu, R., Gao, L., Ma, Y., Wu, D., Yan, X., Jin, X., Wang, Y.-X., Chen, Y., Guo, L., Zhao, Y., Gu, Q., Chen, J., Wang, L., Xu, P., Zhang, W., Zou, D., Biegel, H., Lega, J., McConnell, S., Nagraj, V. P., Guertin, S. L., Hulme-Lowe, C., Turner, S. D., Shi, Y., Ban, X., Walraven, R., Hong, Q.-J., Kong, S., van de Walle, A., Turtle, J. A., Ben-Nun, M., Riley, S., Riley, P., Koyluoglu, U., DesRoches, D., Forli, P., Hamory, B., Kyriakides, C., Leis, H., Milliken, J., Moloney, M., Morgan, J., Nirgudkar, N., Ozcan, G., Piwonka, N., Ravi, M., Schrader, C., Shakhnovich, E., Siegel, D., Spatz, R., Stiefeling, C., Wilkinson, B., Wong, A., Cavany, S., España, G., Moore, S., Oidtman, R., Perkins, A., Kraus, D., Kraus, A., Gao, Z., Bian, J., Cao, W., Lavista Ferres, J., Li, C., Liu, T.-Y., Xie, X., Zhang, S., Zheng, S., Vespignani, A., Chinazzi, M., Davis, J. T., Mu, K., Pastore Y Piontti, A., Xiong, X., Zheng, A., Baek, J., Farias, V., Georgescu, A., Levi, R., Sinha, D., Wilde, J., Perakis, G., Bennouna, M. A., Nze-Ndong, D., Singhvi, D., Spantidakis, I., Thayaparan, L., Tsiourvas, A., Sarker, A., Jadbabaie, A., Shah, D., Della Penna, N., Celi, L. A., Sundar, S., Wolfinger, R., Osthus, D., Castro, L., Fairchild, G., Michaud, I., Karlen, D., Kinsey, M., Mullany, L. C., Rainwater-Lovett, K., Shin, L., Tallaksen, K., Wilson, S., Lee, E. C., Dent, J., Grantz, K. H., Hill, A. L., Kaminsky, J., Kaminsky, K., Keegan, L. T., Lauer, S. A., Lemaitre, J. C., Lessler, J., Meredith, H. R., Perez-Saez, J., Shah, S., Smith, C. P., Truelove, S. A., Wills, J., Marshall, M., Gardner, L., Nixon, K., Burant, J. C., Wang, L., Gao, L., Gu, Z., Kim, M., Li, X., Wang, G., Wang, Y., Yu, S., Reiner, R. C., Barber, R., Gakidou, E., Hay, S. I., Lim, S., Murray, C., Pigott, D., Gurung, H. L., Baccam, P., Stage, S. A., Suchoski, B. T., Prakash, B. A., Adhikari, B., Cui, J., Rodríguez, A., Tabassum, A., Xie, J., Keskinocak, P., Asplund, J., Baxter, A., Oruc, B. E., Serban, N., Arik, S. O., Dusenberry, M., Epshteyn, A., Kanal, E., Le, L. T., Li, C.-L., Pfister, T., Sava, D., Sinha, R., Tsai, T., Yoder, N., Yoon, J., Zhang, L., Abbott, S., Bosse, N. I., Funk, S., Hellewell, J., Meakin, S. R., Sherratt, K., Zhou, M., Kalantari, R., Yamana, T. K., Pei, S., Shaman, J., Li, M. L., Bertsimas, D., Skali Lami, O., Soni, S., Tazi Bouardi, H., Ayer, T., Adee, M., Chhatwal, J., Dalgic, O. O., Ladd, M. A., Linas, B. P., Mueller, P., Xiao, J., Wang, Y., Wang, Q., Xie, S., Zeng, D., Green, A., Bien, J., Brooks, L., Hu, A. J., Jahja, M., McDonald, D., Narasimhan, B., Politsch, C., Rajanala, S., Rumack, A., Simon, N., Tibshirani, R. J., Tibshirani, R., Ventura, V., Wasserman, L., O’Dea, E. B., Drake, J. M., Pagano, R., Tran, Q. T., Ho, L. S. T., Huynh, H., Walker, J. W., Slayton, R. B., Johansson, M. A., Biggerstaff, M. & Reich, N. G.

    Proc. Natl. Acad. Sci. U. S. A. 119, e2113561119 (2022).

  • पब्लिकेशन

    A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan

    Arık, S. Ö., Shor, J., Sinha, R., Yoon, J., Ledsam, J. R., Le, L. T., Dusenberry, M. W., Yoder, N. C., Popendorf, K., Epshteyn, A., Euphrosine, J., Kanal, E., Jones, I., Li, C.-L., Luan, B., Mckenna, J., Menon, V., Singh, S., Sun, M., Ravi, A. S., Zhang, L., Sava, D., Cunningham, K., Kayama, H., Tsai, T., Yoneoka, D., Nomura, S., Miyata, H. & Pfister, T.

    NPJ Digit Med 4, 146 (2021).

  • पब्लिकेशन

    Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks

    Kapoor, A., Ben, X., Liu, L., Perozzi, B., Barnes, M., Blais, M. & O’Banion, S.

    arXiv [cs.LG] (2020).

  • पब्लिकेशन

    Interpretable Sequence Learning for Covid-19 Forecasting

    Arik, Li, Yoon, Sinha, Epshteyn, Le, Menon, Singh, Zhang, Nikoltchev, Sonthalia, Nakhost, Kanal & Pfister.

    Adv. Neural Inf. Process. Syst. 2020.

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