Future studies can build on the study's findings

The gap

Evidence profile

Stated in the cells research gap and cells future research and inline gaps sections of the source papers, classified as general, spanning 4 journals.

Supporting evidence — 5 representative gaps

• Cross-Dataset Deep Learning for Robust Brain Disease Detection and Classification Using Multimodal MRI (2026) · International Journal of Computer Information Systems and Industrial Management Applications · doi

  Brain disease detection and classification using MRI remain challenging due to variations in scanners, acquisition protocols, and disease-specific characteristics. - Most reported models remain benchmarked under narrow, homogeneous experimental conditions. - There is a need for more robust and generalizable deep learning models for brain disease diagnosis.

  generalstated in cells research gap
  Keywords: brain disease detection classification using mri remain challenging
• Cross-Dataset Deep Learning for Robust Brain Disease Detection and Classification Using Multimodal MRI (2026) · International Journal of Computer Information Systems and Industrial Management Applications · doi

  Future research should focus on developing more robust and generalizable deep learning models for brain disease diagnosis. - Future research should investigate the application of the proposed CD-MAFNet model to other medical imaging modalities. - Future research should evaluate the performance of the proposed CD-MAFNet model on larger and more diverse datasets.

  generalstated in cells future research
  Keywords: future research focus developing robust generalizable deep learning
• Uncertainty-Aware Explainable Multimodal AI for Brain Encephalitis (2026) · International Journal of Drug Delivery Technology · doi

  Future work will focus on validating the framework on larger, multi-center datasets and extending it to additional forms of infectious and autoimmune encephalitis. with established medical knowledge and improve clinician trust in AI-assisted diagnosis, addressing a major limitation of traditional black-box deep learning models [7], [10].

  generalstated in inline gapsevidence 5/5
  Keywords: future focus validating framework larger multi center datasets extending additional forms infectious autoimmune encephalitis established
• Generalizable and explainable deep learning for brain MRI: a multi-cohort evaluation of 3D architectures for age and sex prediction (2026) · Brain Informatics · doi

  Future studies can build on the study's findings to develop more robust and generalizable deep learning models for brain MRI analysis. - Future studies can apply the study's methods to other medical imaging applications. - Future studies can investigate the use of other deep learning architectures for brain MRI analysis.

  generalstated in cells future researchevidence 5/5
  Keywords: future studies build study findings develop robust generalizable
• Deep Learning aplicado ao diagnóstico assistido de retinopatia diabética (2026) · Revista ft · doi

  Further research is needed to investigate the use of other deep learning architectures or techniques. - The model should be evaluated in a clinical setting to determine its potential for use in practice. - The use of other datasets or clinical settings should be investigated to determine the generalizability of the model.

  generalstated in cells future researchevidence 4/5
  Keywords: further research needed investigate use other deep learning

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