MedGCN: An IoT-edge thrombus graph convolutional network for accurate prediction and prescription diagnosis of vascular occlusive diseases from unstructured clinical reports

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

(2020) Davide Chicco et al.   BMC GENOMICS

Therapeutic strategies for thrombosis: new targets and approaches

(2020) Nigel Mackman et al.   NATURE REVIEWS DRUG DISCOVERY

IoT medical image detection and rivaroxaban prevent thrombosis in patients with atrial fibrillation

(2020) Liguo Yang et al.   MICROPROCESSORS AND MICROSYSTEMS

IoT in Healthcare: Achieving Interoperability of High-Quality Data Acquired by IoT Medical Devices

(2019) Argyro Mavrogiorgou et al.   SENSORS

SMOTE based class-specific extreme learning machine for imbalanced learning

(2019) Bhagat Singh Raghuwanshi et al.   KNOWLEDGE-BASED SYSTEMS

The study of under- and over-sampling methods’ utility in analysis of highly imbalanced data on osteoporosis

(2017) M. Bach et al.   INFORMATION SCIENCES

Global Burden of Thrombosis: Table.

(2016) Aaron M. Wendelboe et al.   CIRCULATION RESEARCH

A new hybrid filter–wrapper feature selection method for clustering based on ranking

(2016) Saúl Solorio-Fernández et al.   NEUROCOMPUTING

A random forest guided tour

(2016) Gérard Biau et al.   TEST

A random forest guided tour

(2016) Gérard Biau et al.   TEST

Multi-class AdaBoost

(2013) Trevor Hastie et al.   Statistics and Its Interface

Venous and arterial thrombosis: Two aspects of the same disease?

(2010) Paolo Prandoni   Clinical Epidemiology