Results 131 to 140 of about 116,530 (280)

Short Distal Resection Margin Does Not Increase Recurrence Risk After R0 Resection for Rectal Neuroendocrine Tumors: A Single‐Institution Retrospective Study of 208 Patients

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This study evaluated the impact of distal resection margin (DRM) length on recurrence in 208 patients undergoing surgery for rectal neuroendocrine tumors (NETs). Our findings demonstrate that while oncological safety must unquestionably remain the top priority, a short pathological DRM (< 10 mm) does not increase recurrence risk when R0 resection is ...
Kentaro Sato   +8 more
wiley   +1 more source

Risk Factors for Small‐for‐Size Syndrome Grade B/C After Simultaneous Splenectomy in Adult Living‐Donor Liver Transplantation

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
In a single‐center cohort of 577 adult LDLT recipients who underwent simultaneous splenectomy, clinically significant SFSS grade B/C (ILTS‐iLDLT‐LTSI 2023) occurred in 18.2% and was associated with inferior graft survival. Multivariate analysis identified MELD ≥ 30, NLR ≥ 4.5, and donor age ≥ 50 years as independent risk factors, which risk rising ...
Kyohei Yugawa   +6 more
wiley   +1 more source

The role of the COVID-19 impersonal threat strengthening the associations of right-wing attitudes, nationalism and anti-immigrant sentiments. [PDF]

open access: yesCurr Psychol, 2023
Panzeri A   +8 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

open access: yesAdvanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

open access: yesAdvanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson   +6 more
wiley   +1 more source

Accounting conservatism and corporate governance. [PDF]

open access: yes
We predict that firms with stronger corporate governance will exhibit a higher degree of accounting conservatism. Governance level is assessed using a composite measure that incorporates several internal and external characteristics.
García Lara, Juan Manuel   +2 more
core  

Edge Information‐Augmented Auxiliary Diagnosis Method for Cervical Cancer in Medical Decision‐Making Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
To address the problems of insufficient utilization of multiscale features and inefficient feature sharing between tasks in the model, this study proposes an edge‐enhanced intelligent cervical cancer screening method that achieves feature reuse and improves efficiency by jointly optimizing nucleolus segmentation and lesion classification.
Li Wen   +4 more
wiley   +1 more source

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