Alan Karthikesalingam

Orcid: 0009-0000-4958-5976

According to our database1, Alan Karthikesalingam authored at least 33 papers between 2017 and 2024.

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Bibliography

2024
Towards Democratization of Subspeciality Medical Expertise.
CoRR, 2024

Capabilities of Gemini Models in Medicine.
CoRR, 2024

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models.
CoRR, 2024

Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset.
CoRR, 2024

MINT: A wrapper to make multi-modal and multi-image AI models interactive.
CoRR, 2024

Towards Conversational Diagnostic AI.
CoRR, 2024

Conversational AI in health: Design considerations from a Wizard-of-Oz dermatology case study with users, clinicians and a medical LLM.
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

2023
Towards Accurate Differential Diagnosis with Large Language Models.
CoRR, 2023

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation.
CoRR, 2023

The Capability of Large Language Models to Measure Psychiatric Functioning.
CoRR, 2023

Towards Generalist Biomedical AI.
CoRR, 2023

Evaluating AI systems under uncertain ground truth: a case study in dermatology.
CoRR, 2023

Towards Expert-Level Medical Question Answering with Large Language Models.
CoRR, 2023

Generative models improve fairness of medical classifiers under distribution shifts.
CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.
CoRR, 2023

2022
Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions.
Medical Image Anal., 2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.
J. Mach. Learn. Res., 2022

Large Language Models Encode Clinical Knowledge.
CoRR, 2022

Detecting and Preventing Shortcut Learning for Fair Medical AI using Shortcut Testing (ShorT).
CoRR, 2022

Metrics reloaded: Pitfalls and recommendations for image analysis validation.
CoRR, 2022

Robust and Efficient Medical Imaging with Self-Supervision.
CoRR, 2022

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?
CoRR, 2022

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis.
npj Digit. Medicine, 2021

Multitask prediction of organ dysfunction in the intensive care unit using sequential subnetwork routing.
J. Am. Medical Informatics Assoc., 2021

Best of both worlds: local and global explanations with human-understandable concepts.
CoRR, 2021

Supervised Transfer Learning at Scale for Medical Imaging.
CoRR, 2021

Big Self-Supervised Models Advance Medical Image Classification.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Concept-based model explanations for electronic health records.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020
Contrastive Training for Improved Out-of-Distribution Detection.
CoRR, 2020

2019
Evaluation of a digitally-enabled care pathway for acute kidney injury management in hospital emergency admissions.
npj Digit. Medicine, 2019

2018
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy.
CoRR, 2018

2017
Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention.
BMC Medical Informatics Decis. Mak., 2017


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