Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Overview of the ImageCLEF 2017 Tuberculosis Task - Predicting Tuberculosis Type and Drug Resistances
Application of Deep Learning Neural Network for Classification of TB lung CT Images based on Patches
IJREB OPTIMUM – DECISION TREE CLASSIFIER BASED HUMAN INTESTINAL PARASITES CLASSIFICATION
Disease Inference from Health-Related Questions via Sparse Deep Learning
Traditional Feature Engineering and Deep Learning Approaches at Medical Classification Task of ImageCLEF 2016
The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications
Automatic tuberculosis detection using adaptive thresholding in chest radiographs
evaluation of a rapid molecular drug - susceptibility test for tuberculosis .
Microsoft Malware Classification Challenge
automatic medical image annotation in imageclef 2007 : overview , results , and discussion .
A PROGRAMMING INTERFACE FOR MEDICAL DIAGNOSIS PREDICTION
Comparative Study of ID3/C4.5 Decision tree and Multilayer Perceptron Algorithms for the Prediction of Typhoid Fever
A multi-task learning formulation for predicting disease progression
A deep framework for bacterial image segmentation and classification
Survey of Machine Learning Algorithms for Disease Diagnostic
TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References
Diagnosis of extrapulmonary tuberculosis using the Xpert(®) MTB/RIF assay.
Artificial neural network models to support the diagnosis of pleural tuberculosis in adult patients.
An Efficient Algorithm for Disease Prediction with Multi Dimensional Data
Human Microbe-Disease Association Prediction With Graph Regularized Non-Negative Matrix Factorization
Variable host-pathogen compatibility in Mycobacterium tuberculosis
An Investigation of Predictive Profiling from Handwritten Signature Data
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting
Attacks Against BLE Devices by Co-located Mobile Applications
development and validation of the user version of the mobile application rating scale ( umars ) .
EGA — Ethnicity, gender and age, a pre-annotated face database