Study on the influence of combined utilization of air-fog curtain on fully mechanized face DOI
Na Qin, Haiming Yu,

Yuxi Ye

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Сен. 1, 2024

Язык: Английский

A machine learning workflow for large-scale discovery of direct bandgap double perovskites DOI
Yuzhi Chen, Hongyu Liu, Xu Fang

и другие.

Solar Energy Materials and Solar Cells, Год журнала: 2025, Номер 282, С. 113402 - 113402

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

0

The Screening and Diagnosis Technologies Towards Pneumoconiosis: From Imaging Analysis to E-Noses DOI Creative Commons

Y. Zhang,

Wufan Xuan, Shuai Chen

и другие.

Chemosensors, Год журнала: 2025, Номер 13(3), С. 102 - 102

Опубликована: Март 11, 2025

Pneumoconiosis, as the most widely distributed occupational disease globally, poses serious health and social hazards. Its diagnostic techniques have evolved from conventional imaging computer-assisted analysis to emerging sensor strategies covering biomarker analysis, routine breath sensing, integrated electronic nose (E-nose), etc. All of them both special advantages face shortcomings or challenges in practical application. In recent years, emergence advanced data technologies, including artificial intelligence (AI), has provided opportunities for large-scale screening pneumoconiosis. On basis a deep characteristics technologies diagnosis pneumoconiosis, this paper comprehensively systematically reviews current development these especially focusing on research progress provides forecast their future development.

Язык: Английский

Процитировано

0

Deep learning object detection-based early detection of lung cancer DOI Creative Commons
Kuo‐Yang Huang,

Che-Liang Chung,

Jia-Lang Xu

и другие.

Frontiers in Medicine, Год журнала: 2025, Номер 12

Опубликована: Апрель 28, 2025

The early diagnosis and accurate classification of lung cancer have a critical impact on clinical treatment patient survival. rise artificial intelligence technology has led to breakthroughs in medical image analysis. Lung-PET-CT-Dx public dataset was used for the model training evaluation. performance You Only Look Once (YOLO) series models CT object detection task is compared terms algorithms, different versions YOLOv5, YOLOv8, YOLOv9, YOLOv10, YOLOv11 are examined classification. experimental results indicate that prediction YOLOv8 better than those other YOLO versions, with precision rate 90.32% recall 84.91%, which proves can effectively assist physicians improve accuracy disease localization identification.

Язык: Английский

Процитировано

0

Study on the influence of combined utilization of air-fog curtain on fully mechanized face DOI
Na Qin, Haiming Yu,

Yuxi Ye

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

0