Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements
The development, application, and benchmarking of artificial intelligence (AI) tools to
improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid …
improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid …
Brainnet: Precision brain tumor classification with optimized efficientnet architecture
Brain tumors significantly impact human health due to their complexity and the challenges in
early detection and treatment. Accurate diagnosis is crucial for effective intervention, but …
early detection and treatment. Accurate diagnosis is crucial for effective intervention, but …
Diagnosis, treatment, and management of otitis media with artificial intelligence
X Ding, Y Huang, X Tian, Y Zhao, G Feng, Z Gao - Diagnostics, 2023 - mdpi.com
A common infectious disease, otitis media (OM) has a low rate of early diagnosis, which
significantly increases the difficulty of treating the disease and the likelihood of serious …
significantly increases the difficulty of treating the disease and the likelihood of serious …
Artificial cognition for detection of mental disability: a vision transformer approach for Alzheimer's disease
Alzheimer's disease is a common neurological disorder and mental disability that causes
memory loss and cognitive decline, presenting a major challenge to public health due to its …
memory loss and cognitive decline, presenting a major challenge to public health due to its …
Ensemble deep learning technique for detecting MRI brain tumor
The classification process of MRI (magnetic resonance imaging) is frequently used for
making medical diagnoses for conditions including pituitary, glioma, meningioma, and no …
making medical diagnoses for conditions including pituitary, glioma, meningioma, and no …
Automated schizophrenia detection model using blood sample scattergram images and local binary pattern
The main goal of this paper is to advance the field of automated Schizophrenia (SZ)
detection methods by presenting a pioneering feature engineering technique that achieves …
detection methods by presenting a pioneering feature engineering technique that achieves …
Ensemble learning based-features extraction for brain mr images classification with machine learning classifiers
N Remzan, YE Hachimi, K Tahiry, A Farchi - Multimedia Tools and …, 2024 - Springer
In general, different neuroimaging methods including Computed Tomography (CT),
Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET) are …
Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET) are …
Prospects of using machine learning and diamond nanosensing for high sensitivity SARS-CoV-2 diagnosis
SA Qureshi, H Aman, R Schirhagl - Magnetochemistry, 2023 - mdpi.com
The worldwide death toll claimed by Acute Respiratory Syndrome Coronavirus Disease
2019 (SARS-CoV), including its prevailed variants, is 6,812,785 (worldometer. com …
2019 (SARS-CoV), including its prevailed variants, is 6,812,785 (worldometer. com …
Morphological transfer learning based brain tumor detection using YOLOv5
SK Pandey, AK Bhandari - Multimedia Tools and Applications, 2024 - Springer
Medical experts require an efficient tool that provides highly accurate diagnoses of patients
for early and precise detection of the severity of brain tumours using brain magnetic …
for early and precise detection of the severity of brain tumours using brain magnetic …
Lung cancer survival prognosis using a two-stage modeling approach
Lung cancer, the second most prevalent form of cancer with the highest mortality rate,
necessitates the stratification of patients based on their survival rates to develop effective …
necessitates the stratification of patients based on their survival rates to develop effective …