Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms [0.03%]
基于偏心性拓扑描述子的角色，使用监督机器学习算法预测抗HIV药物属性
Shahid Zaman,Wakeel Ahmed,Muhammad Kamran Siddiqui et al.
Shahid Zaman et al.
Chemical graphs are mathematical representations of molecular structures, where atoms are represented as vertices, while chemical bonds are depicted as edges of a graph. The chemical graphs are widely used in cheminformatics to analyze mole...
Lingling Fang,Yongcheng Yu,Shihao Zhang et al.
Lingling Fang et al.
Brain tumors rank among the most devastating diseases in the human body, with their growth potentially resulting in impaired brain tissue function and even life-threatening scenarios, profoundly impacting patients physical and mental well-b...
Enhancing healthcare data security using RFE and CRHSM for big data [0.03%]
使用RFE和CRHSM增强医疗数据安全以实现大数据分析
C Sreedhar,K Mahesh Babu,Suresh Kallam et al.
C Sreedhar et al.
Providing security to the medical big data stored in healthcare cloud systems is the most exciting and demanding task in the present day. Many researchers use cryptographic techniques to protect big data against malicious users/attacks in c...
A data-driven approach to model spatial dose characteristics for catheter placement of high dose-rate brachytherapy for prostate cancer [0.03%]
基于数据驱动的方法来建模前列腺癌高剂量率近距离放射治疗中的导管放置的空间剂量特性
Björn Morén,Hossein Jafarzadeh,Shirin A Enger
Björn Morén
Background: High dose rate brachytherapy (HDR BT) is a common treatment modality for cancer. In HDR BT, a radioactive source is placed inside or close to a tumor, aiming to give a high enough dose to the tumor, while spar...
An adaptive language model-based intelligent medication assistant for the decision support of antidepressant prescriptions [0.03%]
一种基于自适应语言模型的智能药物助手，用于抗抑郁药物处方决策支持
Regina Silva,Luis Gomes
Regina Silva
Background: Depression, a pervasive mental disorder affecting millions worldwide, requires a holistic and personalized approach to treatment. Combining therapy and antidepressant medication is crucial, but selecting the r...
Breast cancer detection and classification: A study on the specification and implementation of multilayer perceptron analog artificial neural networks [0.03%]
乳腺癌的检测和分类：多层感知器模拟人工神经网络的规定和实现研究
Koagne Longpa T Silas,B Djimeli-Tsajio Alain,Noulamo Thierry et al.
Koagne Longpa T Silas et al.
Breast cancer is a leading cause of mortality worldwide. Screening therefore remains the best defense against this disease, highlighting the need for accurate and efficient diagnostic methods. Previous authors addressed this issue by implem...
Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network [0.03%]
使用多案例神经网络实时估算三维血管流体动力学中物理信息约束的作用
Wei Xuan Chan,Wenhao Ding,Binghuan Li et al.
Wei Xuan Chan et al.
Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research to model flow in blood vessels and airways. It is further useful to some clinical applications, such as predicting arterial fractional flow...
Distinguishing severe sleep apnea from habitual snoring using a neck-wearable piezoelectric sensor and deep learning: A pilot study [0.03%]
使用颈部可穿戴压电传感器和深度学习区分严重睡眠呼吸暂停和习惯性打鼾：初步研究
Yi-Ping Chao,Hai-Hua Chuang,Zong-Han Lee et al.
Yi-Ping Chao et al.
This study explores the development of a deep learning model using a neck-wearable piezoelectric sensor to accurately distinguish severe sleep apnea syndrome (SAS) from habitual snoring, addressing the underdiagnosis of SAS in adults. From ...
Explainable machine learning to identify risk factors for unplanned hospital readmissions in Nova Scotian hospitals [0.03%]
可解释机器学习在新斯科舍省医院中识别非计划住院再入院的风险因素
Mariano Maisonnave,Enayat Rajabi,Majid Taghavi et al.
Mariano Maisonnave et al.
Objective: A report from the Canadian Institute for Health Information found unplanned hospital readmissions (UHR) common, costly, and potentially avoidable, estimating a $1.8 billion cost to the Canadian healthcare syste...
SGCLMD: Signed graph-based contrastive learning model for predicting somatic mutation-drug association [0.03%]
基于有符号图对比学习模型的体细胞突变药物关联预测研究
Xiaosong Wang,Haisong Feng,Yilei Zhang et al.
Xiaosong Wang et al.
Somatic mutations could influence critical cellular processes, leading to uncontrolled cell growth and tumor formation. Understanding the intricate interactions between somatic mutations and drugs was crucial for advancing our knowledge of ...