# Deep learning and machine learning for Malaria detection: overview, challenges and future directions

arXiv: https://arxiv.org/abs/2209.13292 · HTML: https://mlsanity.com/paper/2209.13292/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 98 references that are in the map.
- First posted on arXiv 27 Sep 2022.

## Builds on (most cited first, 5 of 5)

- [Densely Connected Convolutional Networks](https://mlsanity.com/paper/1608.06993/) (2016)
- [Going Deeper with Convolutions](https://mlsanity.com/paper/1409.4842/) (2014)
- [A Survey of the Recent Architectures of Deep Convolutional Neural Networks](https://mlsanity.com/paper/1901.06032/) (2019)
- [Reinforcement Learning in Medical Image Analysis: Concepts, Applications, Challenges, and Future Directions](https://mlsanity.com/paper/2206.14302/) (2022)
- [Multilevel Context Representation for Improving Object Recognition](https://mlsanity.com/paper/1703.06408/) (2017)

## Built on by (most cited first, 2 of 2)

- [Convolutional Neural Networks and Vision Transformers for Fashion MNIST Classification: A Literature Review](https://mlsanity.com/paper/2406.03478/) (2024)
- [Exploring the Role of Convolutional Neural Networks (CNN) in Dental Radiography Segmentation: A Comprehensive Systematic Literature Review](https://mlsanity.com/paper/2401.09190/) (2024)

## Abstract (arXiv)

To have the greatest impact, public health initiatives must be made using evidence-based decision-making. Machine learning Algorithms are created to gather, store, process, and analyse data to provide knowledge and guide decisions. A crucial part of any surveillance system is image analysis. The communities of computer vision and machine learning has ended up curious about it as of late. This study uses a variety of machine learning and image processing approaches to detect and forecast the malarial illness. In our research, we discovered the potential of deep learning techniques as smart tools with broader applicability for malaria detection, which benefits physicians by assisting in the diagnosis of the condition. We examine the common confinements of deep learning for computer frameworks and organising, counting need of preparing data, preparing overhead, realtime execution, and explain ability, and uncover future inquire about bearings focusing on these restrictions.