Search Results for author: Adam Mahdi

Found 9 papers, 3 papers with code

Feasibility of machine learning-based rice yield prediction in India at the district level using climate reanalysis data

no code implementations12 Mar 2024 Djavan De Clercq, Adam Mahdi

Yield forecasting, the science of predicting agricultural productivity before the crop harvest occurs, helps a wide range of stakeholders make better decisions around agricultural planning.

Unsupervised Learning Approaches for Identifying ICU Patient Subgroups: Do Results Generalise?

1 code implementation5 Mar 2024 Harry Mayne, Guy Parsons, Adam Mahdi

However, it is unclear whether common patient subgroups exist across different ICUs, which would determine whether ICU restructuring could be operationalised in a standardised manner.

Review of multimodal machine learning approaches in healthcare

no code implementations4 Feb 2024 Felix Krones, Umar Marikkar, Guy Parsons, Adam Szmul, Adam Mahdi

Machine learning methods in healthcare have traditionally focused on using data from a single modality, limiting their ability to effectively replicate the clinical practice of integrating multiple sources of information for improved decision making.

Decision Making

LT-ViT: A Vision Transformer for multi-label Chest X-ray classification

no code implementations13 Nov 2023 Umar Marikkar, Sara Atito, Muhammad Awais, Adam Mahdi

Vision Transformers (ViTs) are widely adopted in medical imaging tasks, and some existing efforts have been directed towards vision-language training for Chest X-rays (CXRs).

Exploring the landscape of large language models in medical question answering

no code implementations11 Oct 2023 Andrew M. Bean, Karolina Korgul, Felix Krones, Robert McCraith, Adam Mahdi

For each question, we score each model on the top-1 accuracy and the distribution of probabilities assigned.

Question Answering

Dual Bayesian ResNet: A Deep Learning Approach to Heart Murmur Detection

1 code implementation Computing in Cardiology 2022 Benjamin Walker, Felix Krones, Ivan Kiskin, Guy Parsons, Terry Lyons, Adam Mahdi

The second model is the output of DBRes integrated with demographic data and signal features using XGBoost. DBRes achieved our best weighted accuracy of $0. 771$ on the hidden test set for murmur classification, which placed us fourth for the murmur task.

Classification

On automatic calibration of the SIRD epidemiological model for COVID-19 data in Poland

no code implementations26 Apr 2022 Piotr Błaszczyk, Konrad Klimczak, Adam Mahdi, Piotr Oprocha, Paweł Potorski, Paweł Przybyłowicz, Michał Sobieraj

We propose a novel methodology for estimating the epidemiological parameters of a modified SIRD model (acronym of Susceptible, Infected, Recovered and Deceased individuals) and perform a short-term forecast of SARS-CoV-2 virus spread.

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