Search Results - "Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing"

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS by Lanchantin, Jack, Singh, Ritambhara, Wang, Beilun, Qi, Yanjun

“…Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification…”
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A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION by Danaee, Padideh, Ghaeini, Reza, Hendrix, David A

“…Cancer detection from gene expression data continues to pose a challenge due to the high dimensionality and complexity of these data. After decades of research…”
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CheXclusion: Fairness gaps in deep chest X-ray classifiers by Seyyed-Kalantari, Laleh, Liu, Guanxiong, McDermott, Matthew, Chen, Irene Y, Ghassemi, Marzyeh

“…Machine learning systems have received much attention recently for their ability to achieve expert-level performance on clinical tasks, particularly in medical…”
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Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders by Way, Gregory P, Greene, Casey S

“…The Cancer Genome Atlas (TCGA) has profiled over 10,000 tumors across 33 different cancer-types for many genomic features, including gene expression levels…”
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MISSING DATA IMPUTATION IN THE ELECTRONIC HEALTH RECORD USING DEEPLY LEARNED AUTOENCODERS by Beaulieu-Jones, Brett K, Moore, Jason H

“…Electronic health records (EHRs) have become a vital source of patient outcome data but the widespread prevalence of missing data presents a major challenge…”
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PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT by Shameer, Khader, Johnson, Kipp W, Yahi, Alexandre, Miotto, Riccardo, Li, L I, Ricks, Doran, Jebakaran, Jebakumar, Kovatch, Patricia, Sengupta, Partho P, Gelijns, Sengupta, Moskovitz, Alan, Darrow, Bruce, David, David L, Kasarskis, Andrew, Tatonetti, Nicholas P, Pinney, Sean, Dudley, Joel T

“…Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia…”
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Large-scale analysis of disease pathways in the human interactome by Agrawal, Monica, Zitnik, Marinka, Leskovec, Jure

“…Discovering disease pathways, which can be defined as sets of proteins associated with a given disease, is an important problem that has the potential to…”
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PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA by Schwartz, H Andrew, Sap, Maarten, Kern, Margaret L, Eichstaedt, Johannes C, Kapelner, Adam, Agrawal, Megha, Blanco, Eduardo, Dziurzynski, Lukasz, Park, Gregory, Stillwell, David, Kosinski, Michal, Seligman, Martin E P, Ungar, Lyle H

“…We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being,…”
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Systematic assessment of analytical methods for drug sensitivity prediction from cancer cell line data by Jang, In Sock, Neto, Elias Chaibub, Guinney, Juistin, Friend, Stephen H, Margolin, Adam A

“…Large-scale pharmacogenomic screens of cancer cell lines have emerged as an attractive pre-clinical system for identifying tumor genetic subtypes with…”
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Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data by Beam, Andrew L, Kompa, Benjamin, Schmaltz, Allen, Fried, Inbar, Weber, Griffin, Palmer, Nathan, Shi, Xu, Cai, Tianxi, Kohane, Isaac S

“…Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this article, we…”
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Unsupervised feature construction and knowledge extraction from genome-wide assays of breast cancer with denoising autoencoders by Tan, Jie, Ung, Matthew, Cheng, Chao, Greene, Casey S

“…Big data bring new opportunities for methods that efficiently summarize and automatically extract knowledge from such compendia. While both supervised learning…”
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Session Introduction: Big Data Imaging Genomics by Kochunov, Peter, Shen, Li, van Horn, John Darrell, Thompson, Paul M

“…This PSB 2022 session addresses challenges and solutions in translating Big Data Imaging Genomics research towards personalized medicine and guiding individual…”
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Improving the explainability of Random Forest classifier - user centered approach by Petkovic, Dragutin, Altman, Russ, Wong, Mike, Vigil, Arthur

“…Machine Learning (ML) methods are now influencing major decisions about patient care, new medical methods, drug development and their use and importance are…”
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MRI to MGMT: predicting methylation status in glioblastoma patients using convolutional recurrent neural networks by Han, Lichy, Kamdar, Maulik R

“…Glioblastoma Multiforme (GBM), a malignant brain tumor, is among the most lethal of all cancers. Temozolomide is the primary chemotherapy treatment for…”
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Crowdsourcing image annotation for nucleus detection and segmentation in computational pathology: evaluating experts, automated methods, and the crowd by Irshad, H, Montaser-Kouhsari, L, Waltz, G, Bucur, O, Nowak, J A, Dong, F, Knoblauch, N W, Beck, A H

“…The development of tools in computational pathology to assist physicians and biomedical scientists in the diagnosis of disease requires access to high-quality…”
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Drug target predictions based on heterogeneous graph inference by Wang, Wenhui, Yang, Sen, Li, Jing

“…A key issue in drug development is to understand the hidden relationships among drugs and targets. Computational methods for novel drug target predictions can…”
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EMPOWERING MULTI-COHORT GENE EXPRESSION ANALYSIS TO INCREASE REPRODUCIBILITY by Haynes, Winston A, Vallania, Francesco, Liu, Charles, Bongen, Erika, Tomczak, Aurelie, Andres-Terrè, Marta, Lofgren, Shane, Tam, Andrew, Deisseroth, Cole A, Li, Matthew D, Sweeney, Timothy E, Khatri, Purvesh

“…A major contributor to the scientific reproducibility crisis has been that the results from homogeneous, single-center studies do not generalize to…”
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Automated disease cohort selection using word embeddings from Electronic Health Records by Glicksberg, Benjamin S, Miotto, Riccardo, Johnson, Kipp W, Shameer, Khader, Li, Li, Chen, Rong, Dudley, Joel T

“…Accurate and robust cohort definition is critical to biomedical discovery using Electronic Health Records (EHR). Similar to prospective study designs, high…”
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Exploiting Domain Knowledge as Causal Independencies in Modeling Gestational Diabetes by Mathur, Saurabh, Karanam, Athresh, Radivojac, Predrag, Haas, David M, Kersting, Kristian, Natarajan, Sriraam

“…We consider the problem of modeling gestational diabetes in a clinical study and develop a domain expert-guided probabilistic model that is both interpretable…”
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ONE-CLASS DETECTION OF CELL STATES IN TUMOR SUBTYPES by Sokolov, Artem, Paull, Evan O, Stuart, Joshua M

“…The cellular composition of a tumor greatly influences the growth, spread, immune activity, drug response, and other aspects of the disease. Tumor cells are…”
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