MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1002/rmb2.12590

Медицинская библиотека · Reproductive medicine and biology · 2024

Potential for artificial intelligence in medicine and its application to male infertility.

Kobayashi Hideyuki

СтатьяОбзорПеревод в очереди

Аннотация

BACKGROUND

The third AI boom, which began in 2010, has been characterized by the rapid evolution and diversification of AI and marked by the development of key technologies such as machine learning and deep learning. AI is revolutionizing the medical field, enhancing diagnostic accuracy, surgical outcomes, and drug production.

METHODS

This review includes explanations of digital transformation (DX), the history of AI, the difference between machine learning and deep learning, recent AI topics, medical AI, and AI research in male infertility.

MAIN FINDINGS

RESULTS

In research on male infertility, I established an AI-based prediction model for Johnsen scores and an AI predictive model for sperm retrieval in non-obstructive azoospermia, both by no-code AI.

CONCLUSIONS

AI is making constant progress. It would be ideal for physicians to acquire a knowledge of AI and even create AI models. No-code AI tools have revolutionized model creation, allowing individuals to independently handle data preparation and model development. Previously a team effort, this shift empowers users to craft customized AI models solo, offering greater flexibility and control in the model creation process.

Для цитирования: Kobayashi Hideyuki. Potential for artificial intelligence in medicine and its application to male infertility.. Reproductive medicine and biology. 2024. DOI: 10.1002/rmb2.12590.
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.