Results 191 to 200 of about 202,193 (268)

Integrative Harmonization of Phenotypic and Genomic Data Improves Bone Mineral Density Prediction in Multi-Study Osteoporosis Research. [PDF]

Genet Epidemiol
Liu A, Liu J, Wu L, Wu Q.
europepmc   +1 more source

Advancing European Plant Variety Registration: Data‐Driven Insights and Stakeholder Perspectives

Agribusiness, EarlyView.
ABSTRACT Efficient plant variety registration is crucial for fostering innovation in the European Union, yet the current regulatory framework is complex and faces calls for reform. This study provides data‐driven evidence to inform the ongoing legislative debate by employing a mixed‐methods approach.
Sergio Urioste Daza, Ibtissem Taghouti, José María Gil Roig   +2 more
wiley   +1 more source

On Window Mean Survival Time With Interval-Censored Data. [PDF]

Stat Med
Iijima T, Momozaki T, Ando S.
europepmc   +1 more source

Independent Prognostic Significance of Perforation in Colorectal Cancer: Insights From a Propensity Score‐Matched Cohort Study

Annals of Gastroenterological Surgery, EarlyView.
Perforated colorectal cancer (PCC) is considered to have a poor prognosis; however, it remains unclear whether this is attributable to perforation itself or to perforation‐related clinicopathological factors. In this study, we analyzed prognosis using propensity score matching with perforation‐related factors and demonstrated that perforation is an ...
Yoshiaki Fujii, Shuhei Ueno, Yoshinaga Aoyama, Hiroyuki Imafuji, Takahisa Hirokawa, Hirotaka Miyai, Masahiro Kimura, Kenji Kobayashi, Shuji Takiguchi   +8 more
wiley   +1 more source

From raw data to actionable insights: preprocessing real-world data for machine learning in diabetes care. [PDF]

Front Digit Health
Montagna M, Rabadzhiev AS, Traverso A, Setola E, Draetta E, Dimonte A, Barbieri S, Fabiani B, Piemonti L, Esposito A, Tacchetti C, Rovere Querini P.   +11 more
europepmc   +1 more source

Multifactor Risk Stratification for Post‐Transplant Alcohol Relapse Using Abstinence, Psychosocial, and Socioeconomic Factors

Annals of Gastroenterological Surgery, EarlyView.
Alcohol relapse after liver transplantation is difficult to predict using abstinence duration alone. We developed a multifactor model integrating abstinence duration, psychosocial risk (SIPAT), and socioeconomic context (AUC 0.70). This approach may support individualized risk assessment and tailored follow‐up intensity; external validation is needed ...
Ayato Obana, Garren Montgomery, Miho Akabane, Matthew Hamilton, Navdeep Singh, Musab Alebrahim, Austin Schenk, Sylvester Black, Kenneth Washburn, Khalid Mumtaz   +9 more
wiley   +1 more source

Protocol to perform cell-type-specific transcriptome-wide association study using scPrediXcan framework. [PDF]

STAR Protoc
Zhou Y, Sumner S, Adeluwa T, Zhu L, Salazar-Magaña S, Kim H, Gona S, Nyasimi F, Kulkarni R, Powell J, Madduri R, Liu B, Chen M, Im HK.   +13 more
europepmc   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

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

Advanced 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

Identifying recurrent stone formers with machine learning: A single-centre observational study. [PDF]

BJUI Compass
Amado P, Fuster DG, Bargagli M, Obrist D, Burkhard F, Roth B, Clavica F, Zheng S.   +7 more
europepmc   +1 more source