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Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care.

Scientific reports
For years, hepatologists have been seeking non-invasive methods able to detect significant liver fibrosis. However, no previous algorithm using routine blood markers has proven to be clinically appropriate in primary care. We present a novel approach...

Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Unhealthy alcohol use represents a major economic burden and cause of morbidity and mortality in the United States. Implementation of interventions for unhealthy alcohol use depends on the availability and accuracy of screening tools. Our group previ...

Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques.

Sensors (Basel, Switzerland)
Leukemia is one of the most dangerous types of malignancies affecting the bone marrow or blood in all age groups, both in children and adults. The most dangerous and deadly type of leukemia is acute lymphoblastic leukemia (ALL). It is diagnosed by he...

An EEG Classification-Based Method for Single-Trial N170 Latency Detection and Estimation.

Computational and mathematical methods in medicine
Event-related potentials (ERPs) can reflect the high-level thinking activities of the brain. In ERP analysis, the superposition and averaging method is often used to estimate ERPs. However, the single-trial ERP estimation can provide researchers with...

Mental speed is high until age 60 as revealed by analysis of over a million participants.

Nature human behaviour
Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. However, response times are not pure measures of mental speed but instead represent the sum of multiple processes. Here we apply a Bayesian diffusion mo...

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods.

Scientific reports
Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schi...

The application research of AI image recognition and processing technology in the early diagnosis of the COVID-19.

BMC medical imaging
BACKGROUND: This study intends to establish a combined prediction model that integrates the clinical symptoms,the lung lesion volume, and the radiomics features of patients with COVID-19, resulting in a new model to predict the severity of COVID-19.