M. Ahmad, Jonathan Reynolds, Y. Rezgui
semanticscholar +1 more source
Machine Learning‐Enhanced Nanoparticle Design for Precision Cancer Drug Delivery
Machine Learning (ML) is revolutionizing cancer nanomedicine by optimizing nanoparticle (NP) design and drug delivery. This review summarizes ML applications across all stages of NP drug delivery, along with a discussion of ongoing challenges and future directions.
Qingquan Wang+5 more
wiley +1 more source
Explaining computation of predictive values: 2 × 2 table versus frequency tree. A randomized controlled trial [ISRCTN74278823] [PDF]
Anke Steckelberg+3 more
openalex +1 more source
Structural Variations Associated with Adaptation and Coat Color in Qinghai‐Tibetan Plateau Cattle
This study reveals the landscape of structural variants in Qinghai‐Tibetan Plateau cattle through long‐read sequencing. Discoveries include metabolic and oxygen‐regulation gene variants, along with a 2‐Mb KIT‐containing inversion and translocations responsible for cattle gray coat. These findings highlight the significant role of structural variants in
Xiaoting Xia+39 more
wiley +1 more source
Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach. [PDF]
Arage FG+5 more
europepmc +1 more source
Limit distribution for the maximum degree of a random recursive tree
William M. Y. Goh, Eric Schmutz
openalex +1 more source
The statistical geometry of scale-free random trees [PDF]
Luca Donetti, C. Destri
openalex +1 more source
Stacking Interventions Enhances Carbon Removals and Profitability of Livestock Production Systems
The study indicates that stacking multiple interventions aimed at maximising soil organic carbon (SOC) sequestration and enteric methane (CH4) reductions realizes greater abatement and profit do any singular intervention, especially when SOC sequestration accounts for a significant proportion of greenhouse gas emissions (GHG) mitigation. Abstract While
My Pham‐Kieu+3 more
wiley +1 more source
The Application of Machine Learning Algorithms to Predict HIV Testing Using Evidence from the 2002-2017 South African Adult Population-Based Surveys: An HIV Testing Predictive Model. [PDF]
Jaiteh M+4 more
europepmc +1 more source
Families of trees decompose the random graph in any arbitrary way
Raphael Yuster
openalex +2 more sources