MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1016/j.compbiomed.2024.108577

Медицинская библиотека · Computers in biology and medicine · 2024

A review of big data technology and its application in cancer care.

Xiao Tianyun, Kong Shanshan, Zhang Zichen, Hua Dianbo, Liu Fengchun

СтатьяОбзорПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

The development of modern medical devices and information technology has led to a rapid growth in the amount of data available for health protection information, with the concept of medical big data emerging globally, along with significant advances in cancer care relying on data-driven approaches. However, outstanding issues such as fragmented data governance, low-quality data specification, and data lock-in still make sharing challenging. Big data technology provides solutions for managing massive heterogeneous data while combining artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) to better mine the intrinsic connections between data. This paper surveys and organizes recent articles on big data technology and its applications in cancer, dividing them into three different types to outline their primary content and summarize their critical role in assisting cancer care. It then examines the latest research directions in big data technology in cancer and evaluates the current state of development of each type of application. Finally, current challenges and opportunities are discussed, and recommendations are made for the further integration of big data technology into the medical industry in the future.

Для цитирования: Xiao Tianyun, Kong Shanshan, Zhang Zichen, Hua Dianbo, Liu Fengchun. A review of big data technology and its application in cancer care.. Computers in biology and medicine. 2024. DOI: 10.1016/j.compbiomed.2024.108577.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.