Work-life balance is often discussed in Japan. Yet surgeons find it challenging to take paternity leave because of their demanding surgical duties and a strong sense of responsibility. One Japanese male surgeon had his first paternity experience as a research fellow in the US. When he returned to Japan, he resumed his surgical training and started a research project to become an academic surgeon. When he and his wife were expecting their second child, they discussed his paternity participation before the delivery and decided on a sustainable paternity participation plan. By coordinating his responsibilities with his co-workers, he limited his attendance at work to daytime hours only for 1 month to manage paternity duties. This adjustment did not affect the number of main and assistant operations conducted that month and effective optimization of workflow processes decreased the extra workload for other team members. His experience suggests that the optimization of workflow processes can enhance personal life, including paternity participation. (150/150).
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00595-024-02959-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The Impact of Artificial Intelligence and Machine Learning in Organ Retrieval and Transplantation: A Comprehensive Review.
Curr Res Transl Med
January 2025
Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, United Kingdom.
This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.
View Article and Find Full Text PDFGreater than the sum of its parts: multimodality imaging in adults with congenital heart disease.
Cardiovasc Diagn Ther
December 2024
Department of Heart, Vascular & Thoracic, Division of Cardiology & Cardiovascular Medicine - Pediatric Cardiology, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA.
As the population of adults with congenital heart disease (ACHD) grows, there also grows an expanded need for non-invasive surveillance methods to guide management and intervention. A multimodal imaging approach layers complementary insights from echocardiography, computed tomography (CT), magnetic resonance imaging (MRI), and other modalities into a clinician's view of patient physiology. Merely applying strategies from acquired adult cardiac disease would be inadequate and potentially misleading.
View Article and Find Full Text PDFAutoGP: An Intelligent Breeding Platform for Enhancing Maize Genomic Selection.
Plant Commun
January 2025
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Hubei, China. Electronic address:
In the face of climate change and the growing global population, there is an urgent need to accelerate the development of high-yielding crop varieties. To this end, vast amounts of genotype-to-phenotype data have been collected, and many machine learning (ML) models have been developed to predict phenotype from a given genotype. However, the requirement for high densities of single-nucleotide polymorphisms (SNPs) and the labor-intensive collection of phenotypic data are hampering the use of these models to advance breeding.
View Article and Find Full Text PDFFully digital workflow for a CAD-CAM custom healing abutment with an optimal emergence profile: A dental technique.
J Prosthet Dent
January 2025
Associate Professor, Department of Prosthodontics, Faculty of Dentistry, Alexandria University, Alexandria, Egypt.
The preoperative fabrication of well-contoured, computer-aided design and computer-aided manufacturing (CAD-CAM), custom healing abutments is essential for guiding soft tissue healing and saving chairside time. This dental technique involves a fully digital workflow to fabricate a CAD-CAM custom healing abutment that relies on preoperative digital implant planning. The healing abutment is designed with an optimal emergence profile that can predictably direct the anatomy of the peri-implant mucosa.
View Article and Find Full Text PDFModular comparison of untargeted metabolomics processing steps.
Anal Chim Acta
January 2025
Christian Doppler Laboratory for Innovative Gut Health Concepts of Livestock, Austria; BOKU University, Vienna, Dept. IFA-Tulln, Institute of Bioanalytics and Agro-Metabolomics, Tulln, Austria.
Background: Untargeted metabolomics requires robust and reliable strategies for data processing to extract relevant information form the underlying raw data. Multiple platforms for data processing are available, but the choice of software tool can have an impact on the analysis. This study provides a comprehensive evaluation of four workflows based on commonly used metabolomics software tools: XCMS, Compound Discoverer, MS-DIAL, and MZmine.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!