Mingming Zhu
Datos Biográficos
| ID | 8001981 |
|---|---|
| NOMBRE | Mingming Zhu |
| NOMBRES | Mingming |
| APELLIDO | Zhu |
| FIRMA | ZHU M |
| AFILIACIONES | Chinese Academy of Meteorological Sciences |
| ORCID | 0000-0002-5978-4992 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 5 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 5 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2023 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 0 |
A nomogram model to predict grade ≥2 acute radiation enteritis in older adult patients with cervical cancer
Introduction Acute Radiation Enteritis (ARE) is a common complication of pelvic radiotherapy, with incidence rates exceeding 60% in older adult populations. Especially, grade ≥2 ARE can lead to treatment interruptions, malnutrition, and even septic shock, thereby impairing patients’ quality of life and survival outcomes. However, existing risk prediction models are predominantly developed based on younger populations or mixed cohorts, lacking sop…
The use of a smartphone application to influence the Knowledge, Attitude, and Practice (KAP) of patients towards a better glaucoma medication compliance
Glaucoma is a chronic eye disease that requires consistent and timely eye drop medication management. However, suboptimal treatment outcomes of glaucoma patients were attributed to poor medication compliance. To address this problem, the study proposed to assess the effectiveness of influencing the Knowledge, Attitude, and Practice (KAP) of the patients with the use of a smartphone application (app) to improve the medication compliance of glaucom…
Learning physically interpretable deep networks from reanalysis data for medium-term regional PM 2.5 forecasts
Medium-term regional forecasts of fine particulate matter (PM 2.5 ) are critical to mitigate its hazardous environmental effects. Deep learning (DL) has recently emerged as a promising technique to improve traditional forecasts based on chemistry-transport models (CTMs). However, challenges remain in (1) representing the complex physics of the PM 2.5 pollution processes including the emission, transport, and chemical conversion of the pollutants,…
UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment
Objective: UAV-based multispectral detection and identification technology for ground injured human targets, is a novel and promising unmanned technology for public health and safety IoT applications, such as outdoor lost injured searching and battlefield casualty searching, and our previous research has demonstrated its feasibility. However, in practical applications, the searched human target always exhibits low target-background contrast relat…
Identification of priority areas for public-access automated external defibrillators (AEDs) in metropolitan areas
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UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment
Objective: UAV-based multispectral detection and identification technology for ground injured human targets, is a novel and promising unmanned technology for public health and safety IoT applications, such as outdoor lost injured searching and battlefield casualty searching, and our previous research has demonstrated its feasibility. However, in practical applications, the searched human target always exhibits low target-background contrast relat…
Identification of priority areas for public-access automated external defibrillators (AEDs) in metropolitan areas
A nomogram model to predict grade ≥2 acute radiation enteritis in older adult patients with cervical cancer
Introduction Acute Radiation Enteritis (ARE) is a common complication of pelvic radiotherapy, with incidence rates exceeding 60% in older adult populations. Especially, grade ≥2 ARE can lead to treatment interruptions, malnutrition, and even septic shock, thereby impairing patients’ quality of life and survival outcomes. However, existing risk prediction models are predominantly developed based on younger populations or mixed cohorts, lacking sop…
The use of a smartphone application to influence the Knowledge, Attitude, and Practice (KAP) of patients towards a better glaucoma medication compliance
Glaucoma is a chronic eye disease that requires consistent and timely eye drop medication management. However, suboptimal treatment outcomes of glaucoma patients were attributed to poor medication compliance. To address this problem, the study proposed to assess the effectiveness of influencing the Knowledge, Attitude, and Practice (KAP) of the patients with the use of a smartphone application (app) to improve the medication compliance of glaucom…
Learning physically interpretable deep networks from reanalysis data for medium-term regional PM 2.5 forecasts
Medium-term regional forecasts of fine particulate matter (PM 2.5 ) are critical to mitigate its hazardous environmental effects. Deep learning (DL) has recently emerged as a promising technique to improve traditional forecasts based on chemistry-transport models (CTMs). However, challenges remain in (1) representing the complex physics of the PM 2.5 pollution processes including the emission, transport, and chemical conversion of the pollutants,…
Geography (3 obras) · Artificial Intelligence (2 obras) · Computer Science (2 obras) · Medicine (2 obras) · Advanced Neural Network Applications (1 obra) · Advanced SAR Imaging Techniques (1 obra) · Air Quality and Health Impacts (1 obra) · Air Quality Monitoring and Forecasting (1 obra) · Anal cancer (1 obra) · Atmospheric and Environmental Gas Dynamics (1 obra)