From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment

K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou - Cell, 2023 - cell.com
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: a systematic review

AM Antoniadi, Y Du, Y Guendouz, L Wei, C Mazo… - Applied Sciences, 2021 - mdpi.com
Machine Learning and Artificial Intelligence (AI) more broadly have great immediate and
future potential for transforming almost all aspects of medicine. However, in many …

Machine learning in additive manufacturing: State-of-the-art and perspectives

C Wang, XP Tan, SB Tor, CS Lim - Additive Manufacturing, 2020 - Elsevier
Additive manufacturing (AM) has emerged as a disruptive digital manufacturing technology.
However, its broad adoption in industry is still hindered by high entry barriers of design for …

The promise of machine learning in predicting treatment outcomes in psychiatry

AM Chekroud, J Bondar, J Delgadillo… - World …, 2021 - Wiley Online Library
For many years, psychiatrists have tried to understand factors involved in response to
medications or psychotherapies, in order to personalize their treatment choices. There is …

Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19

F Shi, J Wang, J Shi, Z Wu, Q Wang… - IEEE reviews in …, 2020 - ieeexplore.ieee.org
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world.
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …

Label-only membership inference attacks

CA Choquette-Choo, F Tramer… - International …, 2021 - proceedings.mlr.press
Membership inference is one of the simplest privacy threats faced by machine learning
models that are trained on private sensitive data. In this attack, an adversary infers whether a …

The ethics of AI in health care: a mapping review

J Morley, CCV Machado, C Burr, J Cowls, I Joshi… - Social Science & …, 2020 - Elsevier
This article presents a mapping review of the literature concerning the ethics of artificial
intelligence (AI) in health care. The goal of this review is to summarise current debates and …

Explaining deep neural networks and beyond: A review of methods and applications

W Samek, G Montavon, S Lapuschkin… - Proceedings of the …, 2021 - ieeexplore.ieee.org
With the broader and highly successful usage of machine learning (ML) in industry and the
sciences, there has been a growing demand for explainable artificial intelligence (XAI) …

Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review

EH Houssein, MM Emam, AA Ali… - Expert Systems with …, 2021 - Elsevier
Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …

Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine

Z Ahmed, K Mohamed, S Zeeshan, XQ Dong - Database, 2020 - academic.oup.com
Precision medicine is one of the recent and powerful developments in medical care, which
has the potential to improve the traditional symptom-driven practice of medicine, allowing …