Area of research
Artificial Intelligence · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include AI in cancer detection, Radiomics and Machine Learning in Medical Imaging, Stellar, planetary, and galactic studies, and Astronomy and Astrophysical Research.
Tremelimumab and durvalumab as neoadjuvant or non-operative management strategy of patients with microsatellite instability-high resectable gastric or gastroesophageal junction adenocarcinoma: the INFINITY study by GONO
Evolving From Discrete Molecular Data Integrations to Actionable Molecular Insights Within the Electronic Health Record.
Use of clinical RNA-sequencing in the detection of actionable fusions compared to DNA-sequencing alone.
Interpretable survival prediction for colorectal cancer using deep learning.
A pan-cancer organoid platform for precision medicine
Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading.
An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.
Reply: 'The importance of study design in the application of artificial intelligence methods in medicine'.
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
The role of social attraction and its link with boldness in the collective movements of three-spined sticklebacks
PLANETARY CANDIDATES OBSERVED BY <i>KEPLER</i> . III. ANALYSIS OF THE FIRST 16 MONTHS OF DATA
FUNDAMENTAL PROPERTIES OF STARS USING ASTEROSEISMOLOGY FROM<i>KEPLER</i>AND<i>CoRoT</i>AND INTERFEROMETRY FROM THE CHARA ARRAY
Oscillation mode frequencies of 61 main-sequence and subgiant stars observed by<i>Kepler</i>
KEPLER-20: A SUN-LIKE STAR WITH THREE SUB-NEPTUNE EXOPLANETS AND TWO EARTH-SIZE CANDIDATES