Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Michail Mamalakis

Research associate (rank 48)

University of Cambridge

United Kingdom

Research Interests

Explore related searches

Professors in United Kingdom Professors in Medical Imaging Medical Imaging professors in United Kingdom

Articles (10)

Year:

2026

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (7)

Ingrid Agartz

University of Oslo

NORWAY

View details

Jonathan Carl Luis Rodrigues

University of Bath

UNITED KINGDOM

View details

Jim Wild

Professor of Magnetic Resonance Physics

University of Sheffield

UNITED KINGDOM

View details

S Ray

Professor

UNITED KINGDOM

View details

Amardeep Ghosh Dastidar

University of Bristol

UNITED KINGDOM

View details

Richard Clayton

Professor of Computational Physiology

University of Sheffield

UNITED KINGDOM

View details

Pankaj Garg

UNITED KINGDOM

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Michail Mamalakis

Research Interests

Explore related searches

Articles (10)

An explainable three dimensional framework to uncover learning patterns: A unified look in variable sulci recognition

Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks

Deep multi-metric training: the need of multi-metric curve evaluation to avoid weak learning

A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy

Improving Prognostication in Pulmonary Hypertension Using AI-quantified Fibrosis and Radiologic Severity Scoring at Baseline CT

Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease

Artificial Intelligence framework with traditional computer vision and deep learning approaches for optimal automatic segmentation of left ventricle with scar

Automatic development of 3D anatomical models of border zone and core scar regions in the left ventricle

A transparent artificial intelligence framework to assess lung disease in pulmonary hypertension

Intra-operative applications of augmented reality in glioma surgery: a systematic review

Collaborators (7)

Ingrid Agartz

Jonathan Carl Luis Rodrigues

Jim Wild

S Ray

Amardeep Ghosh Dastidar

Richard Clayton

Pankaj Garg

Make your next move.