In operational scenarios, steganographers use sets of covers from various sensors and processing pipelines that differ significantly from those used by researchers to train steganalysis models. This leads to an inevitable performance gap when dealing with out-of-distribution covers, commonly referred to as Cover Source Mismatch (CSM). In this study...
In this paper, we study the use of the angle of arrival (AoA) as a feature for performing robust, machine learning (ML)-based physical layer authentication (PLA). In fact, whereas most previous research on PLA relies on physical properties such as channel frequency/impulse response or received signal strength, the use of the AoA in this context has...
Published in Journal of magnetic resonance imaging : JMRI
Idiopathic central precocious puberty (ICPP) impairs child development, without early intervention. The current reference standard, the gonadotropin-releasing hormone stimulation test, is invasive which may hinder diagnosis and intervention. To develop a model for accurate diagnosis of ICPP, by integrating pituitary MRI, carpal bone age, gonadal ul...
Published in Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
This study aimed to investigate the predictive value of coagulation, thromboelastography, stress response, and immune function indicators for the occurrence of deep venous thrombosis (DVT) following radical resection of cervical cancer and ovarian cancer. We conducted a prospective, single-centre, case-control study that included 230 cervical cance...
Published in Molecular ecology
Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human-modified world. Metabarcoding methods make it possible to gather population genetic data for all species wit...
Published in CNS neuroscience & therapeutics
Deficit schizophrenia (DS), defined by primary and enduring negative symptoms, has been proposed as a promising homogeneous subtype of schizophrenia. It has been demonstrated that unimodal neuroimaging characteristics of DS were different from non-deficit schizophrenia (NDS), however, whether multimodal-based neuroimaging features could identify de...
Published in The Journal of thoracic and cardiovascular surgery
Acute kidney injury after cardiac surgery increases morbidity and mortality. Diagnosis relies on oliguria or increased serum creatinine, which develop 48 to 72 hours after injury. We hypothesized machine learning incorporating preoperative, operative, and intensive care unit data could dynamically predict acute kidney injury before conventional ide...
Published in The Laryngoscope
Machine learning (ML) analysis of biometric data in non-controlled environments is underexplored. To evaluate whether ML analysis of physical activity data can be employed to classify whether individuals have postural dysfunction in middle-aged and older individuals. A 1 week period of physical activity was measured by a waist-worn uni-axial accele...
Published in Journal of child psychology and psychiatry, and allied disciplines
The question 'what works for whom' is essential to mental health research, as matching individuals to the treatment best suited to their needs has the potential to maximize the effectiveness of existing approaches. Digitally administered single-session interventions (SSIs) are effective means of reducing depressive symptoms in adolescence, with pot...
Published in The international journal of lower extremity wounds
In a world where automation is becoming increasingly common, easier collection of mass of data and powerful computer processing has meant a transformation in the field of artificial intelligence (AI). The diabetic foot is a multifactorial problem; its issues render it suitable for analysis, interrogation, and development of AI. The latter has the p...
