Computer-Aided detection of tuberculosis from X-ray images using CNN and PatternNet classifier.

Background: Tuberculosis (TB) is a highly infectious disease that mainly affects the human lungs. The gold standard for TB diagnosis is Xpert Mycobacterium tuberculosis/ resistance to rifampicin (MTB/RIF) testing. X-ray, a relatively inexpensive and widely used imaging modality, can be employed as an alternative for early diagnosis of the disease.

A computer-aided diagnosis system for the classification of COVID-19 and non-COVID-19 pneumonia on chest X-ray images by integrating CNN with sparse autoencoder and feed forward neural network.

Several infectious diseases have affected the lives of many people and have caused great dilemmas all over the world. COVID-19 was declared a pandemic caused by a newly discovered virus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by the World Health Organisation in 2019. RT-PCR is considered the golden standard for COVID-19 detection.

Computer-aided detection of COVID-19 from CT scans using an ensemble of CNNs and KSVM classifier.

Corona Virus Disease-2019 (COVID-19) is a global pandemic which is spreading briskly across the globe. The gold standard for the diagnosis of COVID-19 is viral nucleic acid detection with real-time polymerase chain reaction (RT-PCR). However, the sensitivity of RT-PCR in the diagnosis of early-stage COVID-19 is less.

Voluntary perioperative colorectal cancer registry from Kerala-An initial overview.

Background: Although colorectal cancer (CRC) may not be uncommon in India, accurate data regarding its demographics and surgical outcomes is sparse.

Methods: With an aim to assess demographics and perioperative outcomes of CRC in Kerala, all members of Association of Surgical Gastroenterologists of Kerala (ASGK) were invited to participate in a registry. Data of operated cases of CRC were entered on a web-based questionnaire by participating members from January 2016.

Computer-aided detection of COVID-19 from X-ray images using multi-CNN and Bayesnet classifier.

Corona virus disease-2019 (COVID-19) is a pandemic caused by novel coronavirus. COVID-19 is spreading rapidly throughout the world. The gold standard for diagnosing COVID-19 is reverse transcription-polymerase chain reaction (RT-PCR) test.

Computer-aided classification of prostate cancer grade groups from MRI images using texture features and stacked sparse autoencoder.

A novel method to determine the Grade Group (GG) in prostate cancer (PCa) using multi-parametric magnetic resonance imaging (mpMRI) biomarkers is investigated in this paper. In this method, high-level features are extracted from hand-crafted texture features using a deep network of stacked sparse autoencoders (SSAE) and classified them using a softmax classifier (SMC). Transaxial T2 Weighted (T2W), Apparent Diffusion Coefficient (ADC) and high B-Value Diffusion-Weighted (BVAL) images obtained from PROSTATEx-2 2017 challenge dataset are used in this technique.