Reviewing ensemble classification methods in breast cancer
Context Ensemble methods consist of combining more than one single technique to solve
the same task. This approach was designed to overcome the weaknesses of single …
the same task. This approach was designed to overcome the weaknesses of single …
A healthcare monitoring system using random forest and internet of things (IoT)
Abstract The Internet of Things (IoT) enabled various types of applications in the field of
information technology, smart and connected health care is notably a crucial one is one of …
information technology, smart and connected health care is notably a crucial one is one of …
Handling data irregularities in classification: Foundations, trends, and future challenges
Most of the traditional pattern classifiers assume their input data to be well-behaved in terms
of similar underlying class distributions, balanced size of classes, the presence of a full set of …
of similar underlying class distributions, balanced size of classes, the presence of a full set of …
SMILE: Cost-sensitive multi-task learning for nuclear segmentation and classification with imbalanced annotations
High throughput nuclear segmentation and classification of whole slide images (WSIs) is
crucial to biological analysis, clinical diagnosis and precision medicine. With the advances …
crucial to biological analysis, clinical diagnosis and precision medicine. With the advances …
Cost-sensitive learning for imbalanced medical data: a review
Abstract Integrating Machine Learning (ML) in medicine has unlocked many opportunities to
harness complex medical data, enhancing patient outcomes and advancing the field …
harness complex medical data, enhancing patient outcomes and advancing the field …
Diagnosis of heart disease using internet of things and machine learning algorithms
A Kishor, W Jeberson - … of second international conference on computing …, 2021 - Springer
In the current scenario of the digital world, the healthcare industry generates a huge amount
of patient data. Manual handling of these produced data becomes very difficult for doctors …
of patient data. Manual handling of these produced data becomes very difficult for doctors …
Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: a case study
The Covid-19 pandemic has pushed the Intensive Care Units (ICUs) into significant
operational disruptions. The rapid evolution of this disease, the bed capacity constraints, the …
operational disruptions. The rapid evolution of this disease, the bed capacity constraints, the …
Applying data mining techniques to improve breast cancer diagnosis
J Diz, G Marreiros, A Freitas - Journal of medical systems, 2016 - Springer
In the field of breast cancer research, and more than ever, new computer aided diagnosis
based systems have been developed aiming to reduce diagnostic tests false-positives …
based systems have been developed aiming to reduce diagnostic tests false-positives …
On predicting school dropouts in Egypt: A machine learning approach
Compulsory school-dropout is a serious problem affecting not only the education systems,
but also the developmental progress of any country as a whole. Identifying the risk of …
but also the developmental progress of any country as a whole. Identifying the risk of …
[HTML][HTML] Artificial intelligence techniques that may be applied to primary care data to facilitate earlier diagnosis of cancer: systematic review
OT Jones, N Calanzani, S Saji, SW Duffy… - Journal of Medical …, 2021 - jmir.org
Background More than 17 million people worldwide, including 360,000 people in the United
Kingdom, were diagnosed with cancer in 2018. Cancer prognosis and disease burden are …
Kingdom, were diagnosed with cancer in 2018. Cancer prognosis and disease burden are …