[HTML][HTML] Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Mental health is a basic need for a sustainable and developing society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …
financial burden of mental illness have increased globally, and especially in response to …
ECGPsychNet: An optimized hybrid ensemble model for automatic detection of psychiatric disorders using ECG signals
Background. Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and
depression (DPR) are some of the leading causes of disability and suicide worldwide. The …
depression (DPR) are some of the leading causes of disability and suicide worldwide. The …
[HTML][HTML] Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images
This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to
detect various gastrointestinal diseases using a new ResNet50*-based deep feature …
detect various gastrointestinal diseases using a new ResNet50*-based deep feature …
Attention deep feature extraction from brain MRIs in explainable mode: Dgxainet
B Taşcı - Diagnostics, 2023 - mdpi.com
Artificial intelligence models do not provide information about exactly how the predictions
are reached. This lack of transparency is a major drawback. Particularly in medical …
are reached. This lack of transparency is a major drawback. Particularly in medical …
Machine learning models for predicting treatment response in infantile epilepsies
Epilepsy stands as one of the prevalent and significant neurological disorders, representing
a critical healthcare challenge. Recently, machine learning techniques have emerged as …
a critical healthcare challenge. Recently, machine learning techniques have emerged as …
Multilevel hybrid handcrafted feature extraction based depression recognition method using speech
B Taşcı - Journal of Affective Disorders, 2024 - Elsevier
Background and purpose Diagnosis of depression is based on tests performed by
psychiatrists and information provided by patients or their relatives. In the field of machine …
psychiatrists and information provided by patients or their relatives. In the field of machine …
Neural energy computations based on Hodgkin-Huxley models bridge abnormal neuronal activities and energy consumption patterns of major depressive disorder
Y Li, B Zhang, Z Liu, R Wang - Computers in Biology and Medicine, 2023 - Elsevier
Limited by the current experimental techniques and neurodynamical models, the
dysregulation mechanisms of decision-making related neural circuits in major depressive …
dysregulation mechanisms of decision-making related neural circuits in major depressive …
Monocyte/hdl cholesterol ratios as a new inflammatory marker in patients with schizophrenia
Purpose: Monocyte/HDL cholesterol ratio (MHR) is a novel inflammatory marker that is used
as a prognostic factor for cardiovascular diseases and has been studied in many diseases …
as a prognostic factor for cardiovascular diseases and has been studied in many diseases …
Attention TurkerNeXt: Investigations into Bipolar Disorder Detection Using OCT Images
Background and Aim: In the era of deep learning, numerous models have emerged in the
literature and various application domains. Transformer architectures, particularly, have …
literature and various application domains. Transformer architectures, particularly, have …
Detection of brain tumor with a pre-trained deep learning model based on feature selection using MR images
One of the most dangerous diseases in the world is a brain tumor. A brain tumor destroys
healthy tissue in the brain and then multiplies abnormally, causing increased internal …
healthy tissue in the brain and then multiplies abnormally, causing increased internal …