Designing nanotheranostics with machine learning

L Rao, Y Yuan, X Shen, G Yu, X Chen - Nature Nanotechnology, 2024 - nature.com
The inherent limits of traditional diagnoses and therapies have driven the development and
application of emerging nanotechnologies for more effective and safer management of …

[HTML][HTML] Artificial intelligence in healthcare: review and prediction case studies

G Rong, A Mendez, EB Assi, B Zhao, M Sawan - Engineering, 2020 - Elsevier
Artificial intelligence (AI) has been develo** rapidly in recent years in terms of software
algorithms, hardware implementation, and applications in a vast number of areas. In this …

[HTML][HTML] Supervised machine learning models for prediction of COVID-19 infection using epidemiology dataset

LJ Muhammad, EA Algehyne, SS Usman, A Ahmad… - SN computer …, 2021 - Springer
Abstract COVID-19 or 2019-nCoV is no longer pandemic but rather endemic, with more than
651,247 people around world having lost their lives after contracting the disease. Currently …

Trustworthy ai: A computational perspective

H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, Y Liu… - ACM Transactions on …, 2022 - dl.acm.org
In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

Intelligent model to predict early liver disease using machine learning technique

TM Ghazal, AU Rehman, M Saleem… - … for Technology and …, 2022 - ieeexplore.ieee.org
Liver Disease (LD) is the main cause of death worldwide, affecting a large number of
people. A variety of factors affect the liver, resulting in this disease. The diagnosis of this …

eD octor: machine learning and the future of medicine

GS Handelman, HK Kok, RV Chandra… - Journal of internal …, 2018 - Wiley Online Library
Abstract Machine learning (ML) is a burgeoning field of medicine with huge resources being
applied to fuse computer science and statistics to medical problems. Proponents of ML extol …

Machine learning for metabolic engineering: A review

CE Lawson, JM Martí, T Radivojevic… - Metabolic …, 2021 - Elsevier
Abstract Machine learning provides researchers a unique opportunity to make metabolic
engineering more predictable. In this review, we offer an introduction to this discipline in …

Ekiden: A platform for confidentiality-preserving, trustworthy, and performant smart contracts

R Cheng, F Zhang, J Kos, W He… - 2019 IEEE European …, 2019 - ieeexplore.ieee.org
Smart contracts are applications that execute on blockchains. Today they manage billions of
dollars in value and motivate visionary plans for pervasive blockchain deployment. While …

Peering into the black box of artificial intelligence: evaluation metrics of machine learning methods

GS Handelman, HK Kok, RV Chandra… - American Journal of …, 2019 - Am Roentgen Ray Soc
OBJECTIVE. Machine learning (ML) and artificial intelligence (AI) are rapidly becoming the
most talked about and controversial topics in radiology and medicine. Over the past few …

Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease

X Wang, W Huang, L Su, Y **ng, F Jessen… - Molecular …, 2020 - Springer
Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the
Alzheimer's disease (AD) continuum. Investigating populations with SCD is important for …