Predicting Childhood Obesity Using Machine Learning: Practical Considerations [0.03%]
基于机器学习的儿童肥胖预测：实践考量
Erika R Cheng,Rai Steinhardt,Zina Ben Miled
Erika R Cheng
Previous studies demonstrate the feasibility of predicting obesity using various machine learning techniques; however, these studies do not address the limitations of these methods in real-life settings where available data for children may...
Tetanus Severity Classification in Low-Middle Income Countries through ECG Wearable Sensors and a 1D-Vision Transformer [0.03%]
低收入和中等收入国家通过ECG可穿戴传感器和一维视觉变换器进行破伤风严重程度分类
Ping Lu,Zihao Wang,Hai Duong Ha Thi et al.
Ping Lu et al.
Tetanus, a life-threatening bacterial infection prevalent in low- and middle-income countries like Vietnam, impacts the nervous system, causing muscle stiffness and spasms. Severe tetanus often involves dysfunction of the autonomic nervous ...
Towards the Generation of Medical Imaging Classifiers Robust to Common Perturbations [0.03%]
面向抗常见扰动的医学影像分类器生成方法研究
Joshua Chuah,Pingkun Yan,Ge Wang et al.
Joshua Chuah et al.
Background: Machine learning (ML) and artificial intelligence (AI)-based classifiers can be used to diagnose diseases from medical imaging data. However, few of the classifiers proposed in the literature translate to clin...
Strategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging [0.03%]
提高神经影像深度学习分割和分类稳健性和泛化的策略
Anh T Tran,Tal Zeevi,Seyedmehdi Payabvash
Anh T Tran
Artificial Intelligence (AI) and deep learning models have revolutionized diagnosis, prognostication, and treatment planning by extracting complex patterns from medical images, enabling more accurate, personalized, and timely clinical decis...
OutSplice: A Novel Tool for the Identification of Tumor-Specific Alternative Splicing Events [0.03%]
OutSplice：识别肿瘤特异性可变剪接事件的新工具
Joseph Bendik,Sandhya Kalavacherla,Nicholas Webster et al.
Joseph Bendik et al.
Protein variation that occurs during alternative splicing has been shown to play a major role in disease onset and oncogenesis. Due to this, we have developed OutSplice, a user-friendly algorithm to classify splicing outliers in tumor sampl...
Xin Wang,Stacey M Fernandes,Jennifer R Brown et al.
Xin Wang et al.
Immune cell function varies tremendously between individuals, posing a major challenge to emerging cellular immunotherapies. This report pursues the use of cell morphology as an indicator of high-level T cell function. Short-term spreading ...
Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning [0.03%]
基于基因表达数据和机器学习评估卵巢癌化疗反应
Soukaina Amniouel,Keertana Yalamanchili,Sreenidhi Sankararaman et al.
Soukaina Amniouel et al.
Background: Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques gener...
NURR1 Is Differentially Expressed in Breast Cancer According to Patient Racial Identity and Tumor Subtype [0.03%]
NURR1在乳腺癌中的表达受患者种族和肿瘤亚型的影响
Shahensha Shaik,Ha&#x;reanna Campbell,Christopher Williams
Shahensha Shaik
Breast carcinoma (BCa) remains the second most common cause of cancer-related death among American women. Whereas estrogen receptor (ER) expression is typically regarded as a favorable prognostic indicator, a significant proportion of ER(+)...
Meal and Physical Activity Detection from Free-living Data for Discovering Disturbance Patterns to Glucose Levels in People with Diabetes [0.03%]
利用日常活动数据发现糖尿病患者血糖扰动模式的就餐和身体活动检测方法
Mohammad Reza Askari,Mudassir Rashid,Xiaoyu Sun et al.
Mohammad Reza Askari et al.
Objective: Interpretation of time series data collected in free-living has gained importance in chronic disease management. Some data are collected objectively from sensors and some are estimated and entered by the indivi...