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Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers.

Computational and mathematical methods in medicine
Lung cancer has a high mortality rate. Promoting early diagnosis and screening of lung cancer is the most effective way to enhance the survival rate of lung cancer patients. Through computer technology, a comprehensive evaluation of genetic testing r...

Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: Cerebral microbleeds (CMBs) are considered essential indicators for the diagnosis of cerebrovascular disease and cognitive disorders. Traditionally, CMBs are manually interpreted based on criteria including the shape, diameter, and signal ch...

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

Computers in biology and medicine
Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many art...

Deep learning-based automated left ventricular ejection fraction assessment using 2-D echocardiography.

American journal of physiology. Heart and circulatory physiology
Deep learning (DL) has been applied for automatic left ventricle (LV) ejection fraction (EF) measurement, but the diagnostic performance was rarely evaluated for various phenotypes of heart disease. This study aims to evaluate a new DL algorithm for ...

A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG.

PloS one
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most...

Artificial intelligence-based radiomics models in endometrial cancer: A systematic review.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Radiological preoperative assessment of endometrial cancer (EC) is in some cases not precise enough and its performances improvement could lead to a clinical benefit. Radiomics is a recent field of application of artificial intelligence (...

Object and anatomical feature recognition in surgical video images based on a convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence-enabled techniques can process large amounts of surgical data and may be utilized for clinical decision support to recognize or forecast adverse events in an actual intraoperative scenario. To develop an image-guided ...

Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

Histopathology
AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article w...

Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.

Neuroscience letters
The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine learning algorithms to examine patterns of stress-immune networks with cognitive impairment in chronic ...

Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.

Life science alliance
SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that...