AIMC Topic: Female

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Eichner classification based on panoramic X-ray images using deep learning: A pilot study.

Bio-medical materials and engineering
BACKGROUND: Research using panoramic X-ray images using deep learning has been progressing in recent years. There is a need to propose methods that can classify and predict from image information.

Machine learning-based prediction of cerebral oxygen saturation based on multi-modal cerebral oximetry data.

Health informatics journal
This study develops machine learning-based algorithms that facilitate accurate prediction of cerebral oxygen saturation using waveform data in the near-infrared range from a multi-modal oxygen saturation sensor. Data were obtained from 150,000 observ...

Interpretable Machine Learning Models Using Peripheral Immune Cells to Predict 90-Day Readmission or Mortality in Acute Heart Failure Patients.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
BACKGROUND: Acute heart failure (AHF) carries a grave prognosis, marked by high readmission and mortality rates within 90 days post-discharge. This underscores the urgent need for enhanced care transitions, early monitoring, and precise interventions...

Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN).

Journal of X-ray science and technology
BACKGROUND: Connectome is understanding the complex organization of the human brain's structural and functional connectivity is essential for gaining insights into cognitive processes and disorders.

Effects of robot-assisted walking training on balance, motor function, and ADL depending on severity levels in stroke patients.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Despite the explosive increase in interest regarding Robot-Assisted Walking Training (RAWT) for stroke patients, very few studies have divided groups according to the severity levels of patients and conducted studies on the effects of RAW...

Radiomics and Clinical Characters Based Gaussian Naive Bayes (GNB) Model for Preoperative Differentiation of Pulmonary Pure Invasive Mucinous Adenocarcinoma From Mixed Mucinous Adenocarcinoma.

Technology in cancer research & treatment
To develop and validate predictive models based on clinical parameters, and radiomic features to distinguish pulmonary pure invasive mucinous adenocarcinoma (pIMA) from mixed mucinous adenocarcinoma (mIMA) before surgery. From January 2017 to Decem...

hdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning.

Current Alzheimer research
BACKGROUND: Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of β-amyloid plaques and the formation ...

Detection of Muscularis propria Invasion in Urothelial Carcinoma Using Artificial Intelligence.

Technology in cancer research & treatment
Assessment of muscularis propria invasion is a crucial step in the management of urothelial carcinoma since it necessitates aggressive treatment. The diagnosis of muscle invasion is a challenging process for pathologists. Artificial intelligence is ...

Precancerous Change Detection Technique on Mammography Breast Cancer Images based on Mean Ratio and Log Ratio using Fuzzy c Mean Classification with Gabor Filter.

Current medical imaging
BACKGROUND: The growing rate of breast cancer necessitates immediate global attention. Mammography images are used to determine the stage of malignancy. Breast cancer stages must be identified in order to save a person's life.