Giuseppe Bifulco
Biographic Data
| ID | 7794518 |
|---|---|
| NAME | Giuseppe Bifulco |
| GIVEN NAMES | Giuseppe |
| FAMILY NAME | Bifulco |
| SIGNATURE | BIFULCO G |
| AFFILIATIONS | University of Naples Federico II |
| ORCID | 0000-0001-7772-8591 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Use of artificial intelligence to study the hospitalization of women undergoing caesarean section
The study concluded that certain comorbidities, such as cardiovascular disease and preeclampsia, significantly impact LOS following a CS. These findings can assist hospital management in optimizing resource allocation and reducing costs by focusing on the most influential factors
Learning Laparoscopic Radical Hysterectomy
Despite wide screening campaigns and early detection, cervical cancer remains the fourth most common cancer among women. Radical hysterectomy, whether by open, laparoscopic or by robotic-assisted techniques, is the mainstay treatment. However, for adequate surgical results and good oncological prognosis, a gynecological surgeon should be trained to perform those procedures. The learning curve of radical hysterectomy, especially by laparoscopy, is…
No prominent works on this page.
Learning Laparoscopic Radical Hysterectomy
Despite wide screening campaigns and early detection, cervical cancer remains the fourth most common cancer among women. Radical hysterectomy, whether by open, laparoscopic or by robotic-assisted techniques, is the mainstay treatment. However, for adequate surgical results and good oncological prognosis, a gynecological surgeon should be trained to perform those procedures. The learning curve of radical hysterectomy, especially by laparoscopy, is…
Use of artificial intelligence to study the hospitalization of women undergoing caesarean section
The study concluded that certain comorbidities, such as cardiovascular disease and preeclampsia, significantly impact LOS following a CS. These findings can assist hospital management in optimizing resource allocation and reducing costs by focusing on the most influential factors
Medicine (2 works) · Biostatistics (1 work) · Caesarean section (1 work) · Cancer (1 work) · Cancer Risks and Factors (1 work) · Cervical cancer (1 work) · Endometrial and Cervical Cancer Treatments (1 work) · Endometriosis Research and Treatment (1 work) · Epidemiology (1 work) · General surgery (1 work)