Results 151 to 160 of about 259,134 (247)

Prognostic Value of Psoas Major Muscle Volume in Assessing Sarcopenia in Elderly Patients With Rectal Cancer

Annals of Gastroenterological Surgery, EarlyView.
This study investigates the prognostic utility of a novel volumetric indicator—psoas volume index (PVI)—for assessing sarcopenia in elderly rectal cancer patients. Sarcopenia classified by our proposed PVI cut‐off values was associated with poor nutritional and inflammatory status, and patients with low PVI showed significantly worse long‐term outcomes.
Gen Tsujio, Shoichi Manabe, Akio Shiomi, Yusuke Tanaka, Shunsuke Kasai, Tadahiro Kojima, Takahiro Igaki, Yukihiro Mori, Akifumi Notsu   +8 more
wiley   +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

Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer. [PDF]

Sensors (Basel)
Shehzadi T, Ifza I, Liwicki M, Stricker D, Afzal MZ.   +4 more
europepmc   +1 more source

Evaluation of Experienced Manipulation Characteristics in Robotic Surgery Using Log Data From the Hinotori Surgical System

Annals of Gastroenterological Surgery, EarlyView.
This study analyzed log data from the Japanese hinotori surgical robot to characterize manipulation performed by experienced surgeons in robotic surgery. Compared with less‐experienced surgeons, the experienced group demonstrated shorter task durations, reduced travel distances with the right instrument (Arm3), faster and more dynamically modulated ...
Masaki Saito, Shunsuke Hayakawa, Hiroyuki Sagawa, Tamiaki Kondo, Masanao Ohashi, Sunao Ito, Reo Sato, Hajime Ushigome, Kenta Saito, Ryo Ogawa, Hiroki Takahashi, Shuji Takiguchi   +11 more
wiley   +1 more source

Spheres, tears, and spears: Regulating the perimeter and circularity of millimeter‐sized alginate hydrogel beads

AIChE Journal, EarlyView.
Abstract Generating hydrogel beads pertains to many engineering applications. We examined two alginate‐based fluids at three concentrations of alginate, cAG$$ {c}_{\mathrm{AG}} $$. We used the “Map of Misery” to determine which material property (viscosity, elasticity, and inertia) drives droplet formation.
Conor G. Harris, Katherine D. Bandettini, Hannah K. Gedde, Lewis Semprini, Kaitlin C. Fogg, Willie E. Rochefort   +5 more
wiley   +1 more source

Traditional cloud pattern classification algorithm based on semi-supervision with Random Line Augment. [PDF]

Sci Rep
Chen C, Wang H.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 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

Measured multi-source semi-supervised working condition recognition based on curvelet pooling and attention mechanism learning. [PDF]

Sci Rep
Yang S, Zhou B, Wang Y, Liu W.
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source