Deep learning for healthcare: review, opportunities and challenges

R Miotto, F Wang, S Wang, X Jiang… - Briefings in …, 2018 - academic.oup.com
Gaining knowledge and actionable insights from complex, high-dimensional and
heterogeneous biomedical data remains a key challenge in transforming health care …

Privacy and human behavior in the age of information

A Acquisti, L Brandimarte, G Loewenstein - Science, 2015 - science.org
This Review summarizes and draws connections between diverse streams of empirical
research on privacy behavior. We use three themes to connect insights from social and …

On the opportunities and risks of foundation models

R Bommasani, DA Hudson, E Adeli, R Altman… - ar** personalized diagnostic strategies and targeted treatments requires a deep
understanding of disease biology and the ability to dissect the relationship between …

[HTML][HTML] Deep patient: an unsupervised representation to predict the future of patients from the electronic health records

R Miotto, L Li, BA Kidd, JT Dudley - Scientific reports, 2016 - nature.com
Secondary use of electronic health records (EHRs) promises to advance clinical research
and better inform clinical decision making. Challenges in summarizing and representing …

[BOOK][B] Antifragile: Things that gain from disorder

NN Taleb - 2014 - books.google.com
Antifragile is a standalone book in Nassim Nicholas Taleb's landmark Incerto series, an
investigation of opacity, luck, uncertainty, probability, human error, risk, and decision-making …

Deep learning in drug discovery: an integrative review and future challenges

H Askr, E Elgeldawi, H Aboul Ella… - Artificial Intelligence …, 2023 - Springer
Recently, using artificial intelligence (AI) in drug discovery has received much attention
since it significantly shortens the time and cost of develo** new drugs. Deep learning (DL) …

Toward better drug discovery with knowledge graph

X Zeng, X Tu, Y Liu, X Fu, Y Su - Current opinion in structural biology, 2022 - Elsevier
Drug discovery is the process of new drug identification. This process is driven by the
increasing data from existing chemical libraries and data banks. The knowledge graph is …

Network-based prediction of drug combinations

F Cheng, IA Kovács, AL Barabási - Nature communications, 2019 - nature.com
Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an
important role in treating multiple complex diseases. Yet, our ability to identify and validate …