Exosomes as a new frontier of cancer liquid biopsy

D Yu, Y Li, M Wang, J Gu, W Xu, H Cai, X Fang… - Molecular cancer, 2022 - Springer
Liquid biopsy, characterized by minimally invasive detection through biofluids such as
blood, saliva, and urine, has emerged as a revolutionary strategy for cancer diagnosis and …

The role of artificial intelligence in early cancer diagnosis

B Hunter, S Hindocha, RW Lee - Cancers, 2022 - mdpi.com
Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …

Application of artificial intelligence in food industry—a guideline

NR Mavani, JM Ali, S Othman, MA Hussain… - Food Engineering …, 2022 - Springer
Artificial intelligence (AI) has embodied the recent technology in the food industry over the
past few decades due to the rising of food demands in line with the increasing of the world …

Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis

Y Xiao, M Bi, H Guo, M Li - EBioMedicine, 2022 - thelancet.com
Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the
poorest prognosis among gynecological malignancies. Because of the absence of specific …

Utilizing convolutional neural networks to classify monkeypox skin lesions

EHI Eliwa, AM El Koshiry, T Abd El-Hafeez… - Scientific reports, 2023 - nature.com
Monkeypox is a rare viral disease that can cause severe illness in humans, presenting with
skin lesions and rashes. However, accurately diagnosing monkeypox based on visual …

Machine learning models for the identification of prognostic and predictive cancer biomarkers: a systematic review

Q Al-Tashi, MB Saad, A Muneer, R Qureshi… - International journal of …, 2023 - mdpi.com
The identification of biomarkers plays a crucial role in personalized medicine, both in the
clinical and research settings. However, the contrast between predictive and prognostic …

Artificial intelligence in gynecologic cancers: Current status and future challenges–A systematic review

M Akazawa, K Hashimoto - Artificial Intelligence in Medicine, 2021 - Elsevier
Objective Over the past years, the application of artificial intelligence (AI) in medicine has
increased rapidly, especially in diagnostics, and in the near future, the role of AI in medicine …

Heterogeneity and treatment landscape of ovarian carcinoma

AC Veneziani, E Gonzalez-Ochoa, H Alqaisi… - Nature Reviews …, 2023 - nature.com
Ovarian carcinoma is characterized by heterogeneity at the molecular, cellular and
anatomical levels, both spatially and temporally. This heterogeneity affects response to …

A meta-analysis of Watson for Oncology in clinical application

Z Jie, Z Zhiying, L Li - Scientific reports, 2021 - nature.com
Using the method of meta-analysis to systematically evaluate the consistency of treatment
schemes between Watson for Oncology (WFO) and Multidisciplinary Team (MDT), and to …

The coming of age of AI/ML in drug discovery, development, clinical testing, and manufacturing: The FDA Perspectives

SK Niazi - Drug Design, Development and Therapy, 2023 - Taylor & Francis
Artificial intelligence (AI) and machine learning (ML) represent significant advancements in
computing, building on technologies that humanity has developed over millions of years …