Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis

Z Bahroun, C Anane, V Ahmed, A Zacca - Sustainability, 2023 - mdpi.com
In the ever-evolving era of technological advancements, generative artificial intelligence
(GAI) emerges as a transformative force, revolutionizing education. This review paper …

A guide to artificial intelligence for cancer researchers

R Perez-Lopez, N Ghaffari Laleh, F Mahmood… - Nature Reviews …, 2024 - nature.com
Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …

Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology

M Aversa, G Nobis, M Hägele… - Advances in …, 2023 - proceedings.neurips.cc
We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large
histological images while preserving long-range correlation structural information. Our …

An overview and a roadmap for artificial intelligence in hematology and oncology

W Rösler, M Altenbuchinger, B Baeßler… - Journal of cancer …, 2023 - Springer
Background Artificial intelligence (AI) is influencing our society on many levels and has
broad implications for the future practice of hematology and oncology. However, for many …

Artificial intelligence in clinical oncology: from data to digital pathology and treatment

K Senthil Kumar, V Miskovic, A Blasiak… - American Society of …, 2023 - ascopubs.org
Recently, a wide spectrum of artificial intelligence (AI)–based applications in the broader
categories of digital pathology, biomarker development, and treatment have been explored …

Slideflow: deep learning for digital histopathology with real-time whole-slide visualization

JM Dolezal, S Kochanny, E Dyer, S Ramesh… - BMC …, 2024 - Springer
Deep learning methods have emerged as powerful tools for analyzing histopathological
images, but current methods are often specialized for specific domains and software …

Generating and evaluating synthetic data in digital pathology through diffusion models

M Pozzi, S Noei, E Robbi, L Cima, M Moroni… - Scientific Reports, 2024 - nature.com
Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks
like data augmentation and addressing data scarcity and privacy. However, its use …

Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features

FM Howard, HM Hieromnimon, S Ramesh… - Science …, 2024 - science.org
Artificial intelligence models have been increasingly used in the analysis of tumor histology
to perform tasks ranging from routine classification to identification of molecular features …

Intraoperative detection of parathyroid glands using artificial intelligence: optimizing medical image training with data augmentation methods

JH Lee, EK Ku, YS Chung, YJ Kim, KG Kim - Surgical Endoscopy, 2024 - Springer
Background Postoperative hypoparathyroidism is a major complication of thyroidectomy,
occurring when the parathyroid glands are inadvertently damaged during surgery. Although …

Develo** a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning

D Choudhury, JM Dolezal, E Dyer, S Kochanny… - …, 2024 - thelancet.com
Background Deployment and access to state-of-the-art precision medicine technologies
remains a fundamental challenge in providing equitable global cancer care in low-resource …