AIMC Topic: Female

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Deep neural networks with promising diagnostic accuracy for the classification of atypical femoral fractures.

Acta orthopaedica
Background and purpose - A correct diagnosis is essential for the appropriate treatment of patients with atypical femoral fractures (AFFs). The diagnostic accuracy of radiographs with standard radiology reports is very poor. We derived a diagnostic a...

Prediction of cerebral perfusion pressure during CPR using electroencephalogram in a swine model of ventricular fibrillation.

The American journal of emergency medicine
BACKGROUND: Measuring the quality of cardiopulmonary resuscitation (CPR) is important for improving outcomes in cardiac arrest. Cerebral perfusion pressure (CePP) could represent cerebral circulation during CPR, but it is difficult to measure non-inv...

Artificial neural network and logistic regression modelling to characterize COVID-19 infected patients in local areas of Iran.

Biomedical journal
BACKGROUND: COVID-19 is an infectious disease that started spreading globally at the end of 2019. Due to differences in patient characteristics and symptoms in different regions, in this research, a comparative study was performed on COVID-19 patient...

Diagnostic Performance of Deep Learning-Based Lesion Detection Algorithm in CT for Detecting Hepatic Metastasis from Colorectal Cancer.

Korean journal of radiology
OBJECTIVE: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists.

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells.

Annals of neurology
In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced plu...

An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses.

Ultrasonic imaging
Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis c...

Fear Recognition for Women Using a Reduced Set of Physiological Signals.

Sensors (Basel, Switzerland)
Emotion recognition is benefitting from the latest research into physiological monitoring and wireless communications, among other remarkable achievements. These technologies can indeed provide solutions to protect vulnerable people in scenarios such...

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Scientific reports
Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial inte...

Machine learning based predictors for COVID-19 disease severity.

Scientific reports
Predictors of the need for intensive care and mechanical ventilation can help healthcare systems in planning for surge capacity for COVID-19. We used socio-demographic data, clinical data, and blood panel profile data at the time of initial presentat...

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm.

Critical care (London, England)
BACKGROUND: Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some pr...