Zobrazeno 1 - 10
of 6 165
pro vyhledávání: '"Partin, A."'
Autor:
Overbeek, Jamie C., Partin, Alexander, Brettin, Thomas S., Chia, Nicholas, Narykov, Oleksandr, Vasanthakumari, Priyanka, Wilke, Andreas, Zhu, Yitan, Clyde, Austin, Jones, Sara, Gnanaolivu, Rohan, Liu, Yuanhang, Jiang, Jun, Wang, Chen, Knutson, Carter, McNaughton, Andrew, Kumar, Neeraj, Fernando, Gayara Demini, Ghosh, Souparno, Sanchez-Villalobos, Cesar, Zhang, Ruibo, Pal, Ranadip, Weil, M. Ryan, Stevens, Rick L.
Cancer drug response prediction (DRP) models present a promising approach towards precision oncology, tailoring treatments to individual patient profiles. While deep learning (DL) methods have shown great potential in this area, models that can be su
Externí odkaz:
http://arxiv.org/abs/2409.12215
Autor:
Feng, Tianshu, Gnanaolivu, Rohan, Safikhani, Abolfazl, Liu, Yuanhang, Jiang, Jun, Chia, Nicholas, Partin, Alexander, Vasanthakumari, Priyanka, Zhu, Yitan, Wang, Chen
Human cancers present a significant public health challenge and require the discovery of novel drugs through translational research. Transcriptomics profiling data that describes molecular activities in tumors and cancer cell lines are widely utilize
Externí odkaz:
http://arxiv.org/abs/2407.04486
Autor:
Vasanthakumari, Priyanka, Brettin, Thomas, Zhu, Yitan, Yoo, Hyunseung, Shukla, Maulik, Partin, Alexander, Xia, Fangfang, Narykov, Oleksandr, Stevens, Rick L.
Informed selection of drug candidates for laboratory experimentation provides an efficient means of identifying suitable anti-cancer treatments. The advancement of artificial intelligence has led to the development of computational models to predict
Externí odkaz:
http://arxiv.org/abs/2310.11329
Efficient delivery of current from PCB to point-of-load (POL) is a primary concern in modern high-power high-density integrated systems. Traditionally, a 48 V power signal is converted to the low, POL voltage at the board and/or package level. As int
Externí odkaz:
http://arxiv.org/abs/2309.10141
Autor:
Partin, Alexander, Brettin, Thomas S., Zhu, Yitan, Narykov, Oleksandr, Clyde, Austin, Overbeek, Jamie, Stevens, Rick L.
Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improvin
Externí odkaz:
http://arxiv.org/abs/2211.10442
Publikováno v:
Medical Education Online, Vol 29, Iss 1 (2024)
In this rapid communication, accelerated undergraduate medical education is examined using prior literature as well as experiences of those who have completed or are in the process of completing accelerated medical curricula. The Consortium of Accele
Externí odkaz:
https://doaj.org/article/a2e3e718d7b3482bb6eeb3c9c31e93d6
We analyze the regression accuracy of convolutional neural networks assembled from encoders, decoders and skip connections and trained with multifidelity data. Besides requiring significantly less trainable parameters than equivalent fully connected
Externí odkaz:
http://arxiv.org/abs/2205.05187
Autor:
Partin, Alexander, Brettin, Thomas, Zhu, Yitan, Dolezal, James M., Kochanny, Sara, Pearson, Alexander T., Shukla, Maulik, Evrard, Yvonne A., Doroshow, James H., Stevens, Rick L.
Patient-derived xenografts (PDXs) are an appealing platform for preclinical drug studies because the in vivo environment of PDXs helps preserve tumor heterogeneity and usually better mimics drug response of patients with cancer compared to CCLs. We i
Externí odkaz:
http://arxiv.org/abs/2204.11678
Autor:
Partin, Camille A., McDonald, Brayden S., McConnell, Michael, Thrane, Kristine, Graham Pearson, D., Sarkar, Chiranjeeb, Luo, Yan, Stern, Richard A.
Publikováno v:
In Gondwana Research October 2024 134:222-244
Novel Magnetic Resonance (MR) imaging modalities can quantify hemodynamics but require long acquisition times, precluding its widespread use for early diagnosis of cardiovascular disease. To reduce the acquisition times, reconstruction methods from u
Externí odkaz:
http://arxiv.org/abs/2201.03715