Zobrazeno 1 - 10
of 147
pro vyhledávání: '"Nasr Mohammad"'
Autor:
Pham, Thuong Le Hoai, Saurav, Jillur Rahman, Omere, Aisosa A., Heyl, Calvin J., Nasr, Mohammad Sadegh, Reynolds, Cody Tyler, Veerla, Jai Prakash Yadav, Shang, Helen H, Jaworski, Justyn, Ravenscraft, Alison, Buonomo, Joseph Anthony, Luber, Jacob M.
We introduce a protein language model for determining the complete sequence of a peptide based on measurement of a limited set of amino acids. To date, protein sequencing relies on mass spectrometry, with some novel edman degregation based platforms
Externí odkaz:
http://arxiv.org/abs/2408.00892
Autor:
Veerla, Jai Prakash, Guttikonda, Partha Sai, Hajighasemi, Amir, Saurav, Jillur Rahman, Darji, Aarti, Reynolds, Cody T., Mohamed, Mohamed, Nasr, Mohammad S., Shang, Helen H., Luber, Jacob M.
In contemporary pathology, multiplexed immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) present both significant opportunities and challenges. These methodologies shed light on intricate tumor microenvironment interactions, emphasiz
Externí odkaz:
http://arxiv.org/abs/2401.02882
Autor:
Thota, Poojitha, Veerla, Jai Prakash, Guttikonda, Partha Sai, Nasr, Mohammad S., Nilizadeh, Shirin, Luber, Jacob M.
In the context of medical artificial intelligence, this study explores the vulnerabilities of the Pathology Language-Image Pretraining (PLIP) model, a Vision Language Foundation model, under targeted attacks. Leveraging the Kather Colon dataset with
Externí odkaz:
http://arxiv.org/abs/2401.02565
Autor:
Malidarreh, Parisa Boodaghi, Rout, Biraaj, Nasr, Mohammad Sadegh, Borad, Priyanshi, Saurav, Jillur Rahman, Veerla, Jai Prakash, Fenelon, Kelli, Koromila, Theodora, Luber, Jacob M.
In this paper, we introduce a pipeline based on Random Forest Regression to predict the future distribution of cells that are expressed by the Sog-D gene (active cells) in both the Anterior to posterior (AP) and the Dorsal to Ventral (DV) axis of the
Externí odkaz:
http://arxiv.org/abs/2401.02564
Autor:
Vora, Neel R, Hajighasemi, Amir, Reynolds, Cody T., Radmehr, Amirmohammad, Mohamed, Mohamed, Saurav, Jillur Rahman, Aziz, Abdul, Veerla, Jai Prakash, Nasr, Mohammad S, Lotspeich, Hayden, Guttikonda, Partha Sai, Pham, Thuong, Darji, Aarti, Malidarreh, Parisa Boodaghi, Shang, Helen H, Harvey, Jay, Ding, Kan, Nguyen, Phuc, Luber, Jacob M
Head-based signals such as EEG, EMG, EOG, and ECG collected by wearable systems will play a pivotal role in clinical diagnosis, monitoring, and treatment of important brain disorder diseases. However, the real-time transmission of the significant cor
Externí odkaz:
http://arxiv.org/abs/2312.12587
Autor:
Shang, Helen H., Nasr, Mohammad Sadegh, Veerla, Jai Prakash, Malidarreh, Parisa Boodaghi, Saurav, MD Jillur Rahman, Hajighasemi, Amir, Huber, Manfred, Moleta, Chace, Makker, Jitin, Luber, Jacob M.
The search and retrieval of digital histopathology slides is an important task that has yet to be solved. In this case study, we investigate the clinical readiness of three state-of-the-art histopathology slide search engines, Yottixel, SISH, and Ret
Externí odkaz:
http://arxiv.org/abs/2306.17019
Autor:
Robben, Michael, Hajighasemi, Amir, Nasr, Mohammad Sadegh, Veerla, Jai Prakesh, Alsup, Anne M., Rout, Biraaj, Shang, Helen H., Fowlds, Kelli, Malidarreh, Parisa Boodaghi, Koomey, Paul, Saurav, MD Jillur Rahman, Luber, Jacob M.
Publikováno v:
F1000Research 2023, 12:1436
Artificial intelligence represents a new frontier in human medicine that could save more lives and reduce the costs, thereby increasing accessibility. As a consequence, the rate of advancement of AI in cancer medical imaging and more particularly tis
Externí odkaz:
http://arxiv.org/abs/2306.16989
Autor:
Hajighasemi, Amir, Saurav, MD Jillur Rahman, Nasr, Mohammad S, Veerla, Jai Prakash, Darji, Aarti, Malidarreh, Parisa Boodaghi, Robben, Michael, Shang, Helen H, Luber, Jacob M
We present an approach for multimodal pathology image search, using dynamic time warping (DTW) on Variational Autoencoder (VAE) latent space that is fed into a ranked choice voting scheme to retrieve multiplexed immunofluorescent imaging (mIF) that i
Externí odkaz:
http://arxiv.org/abs/2306.06780
Autor:
Nasr, Mohammad Sadegh, Hajighasemi, Amir, Koomey, Paul, Malidarreh, Parisa Boodaghi, Robben, Michael, Saurav, Jillur Rahman, Shang, Helen H., Huber, Manfred, Luber, Jacob M.
Publikováno v:
2023 IEEE ISBI, Cartagena, Colombia, 2023, pp. 1-5
In this paper, we introduce a Variational Autoencoder (VAE) based training approach that can compress and decompress cancer pathology slides at a compression ratio of 1:512, which is better than the previously reported state of the art (SOTA) in the
Externí odkaz:
http://arxiv.org/abs/2303.13332
Autor:
Saurav, Jillur Rahman, Nasr, Mohammad Sadegh, Koomey, Paul, Robben, Michael, Huber, Manfred, Weidanz, Jon, Ryan, Bríd, Ruppin, Eytan, Jiang, Peng, Luber, Jacob M.
Publikováno v:
2023 IEEE CIBCB, Eindhoven, Netherlands, 2023, pp. 1-8
Here we present a structural similarity index measure (SSIM) guided conditional Generative Adversarial Network (cGAN) that generatively performs image-to-image (i2i) synthesis to generate photo-accurate protein channels in multiplexed spatial proteom
Externí odkaz:
http://arxiv.org/abs/2205.10373