AIMC Topic: Female

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Learning from data to predict future symptoms of oncology patients.

PloS one
Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient's treatment regimen more ...

Association between prenatal exposure to multiple persistent organic pollutants (POPs) and growth indicators in newborns.

Environmental research
Despite the fact that many of persistent organic pollutants (POPs) have been banned for decades, they still constitute a group of harmful substances to human health. Prenatal exposure can have adverse effects on one's health as well as on their newbo...

Renal Function Impairment in Kidney Transplantation: Importance of Early BK Virus Detection.

Transplantation proceedings
BACKGROUND: BK virus allograft nephropathy is a major complication of kidney transplantation that markedly reduces graft survival (50% graft failure 24 months after being diagnosed). BK virus replication can occur at any time posttransplantation. Vir...

Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.

Clinical lung cancer
INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive o...

Disposition of ceftizoxime in Staphylococcal mastitis in Indian crossbred cows.

Veterinary journal (London, England : 1997)
Disposition of ceftizoxime was studied in Indian crossbred cows following a single IV dosing in field conditions. Six healthy lactating and six mastitic crossbred cows were assigned to two groups (Group 1 and Group 2). A single IV administration of c...

Prediction of fatty liver disease using machine learning algorithms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for preven...

Machine learning for detecting moyamoya disease in plain skull radiography using a convolutional neural network.

EBioMedicine
BACKGROUND: Recently, innovative attempts have been made to identify moyamoya disease (MMD) by focusing on the morphological differences in the head of MMD patients. Following the recent revolution in the development of deep learning (DL) algorithms,...

A Single Session of Robot-Controlled Proprioceptive Training Modulates Functional Connectivity of Sensory Motor Networks and Improves Reaching Accuracy in Chronic Stroke.

Neurorehabilitation and neural repair
BACKGROUND: Passive robot-generated arm movements in conjunction with proprioceptive decision making and feedback modulate functional connectivity (FC) in sensory motor networks and improve sensorimotor adaptation in normal individuals. This proof-of...

Model based on GA and DNN for prediction of mRNA-Smad7 expression regulated by miRNAs in breast cancer.

Theoretical biology & medical modelling
BACKGROUND: The Smad7 protein is negative regulator of the TGF-β signaling pathway, which is upregulated in patients with breast cancer. miRNAs regulate proteins expressions by arresting or degrading the mRNAs. The purpose of this work is to identify...

Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk.

BMC medical research methodology
BACKGROUND: The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML m...