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Articles by Roy SK
Evaluating video-based synthetic data for training lightweight models in strawberry leaf disease classification
Evaluating video-based synthetic data for training lightweight models in strawberry leaf disease classification Department of Industrial Engineering, Faculty of Engineering-Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia DOI 10.7717/peerj-cs.3521 Academic Editor Nicole Nogoy Subject Areas Algorithms and Analysis of Algorithms, Artificial Intelligence, Computer Vision, Data Mining and Machine Learning, Neural Networks Keywords Video synthetic data, Lightweight models, Precision...
A decision support framework for optimizing career path prediction and vocational mobility of college graduates
Vocational mobility (VM), which means the freedom of individuals to move easily from one opportunity to another, is an essential factor that enhances personal career development within a volatile job market (Mavlankulovich, 2024). The emergence and continued growth of various industries due to globalization and technological advancements have compounded the need for college graduates to provide reasoned actions while making multi-step career choices.
Design of performance evaluation method for higher education reform based on adaptive fuzzy algorithm
In the construction of universities, the construction of the teaching staff plays a decisive role in the quality of teaching, which directly affects the level of education and the quality of student training (Hussain et al., 2023; Abdallah & Abdallah, 2023).
Attention-based BiLSTM-XGBoost model for reliability assessment and lifetime prediction of digital microfluidic systems
Digital microfluidic (DMF) systems based on electrowetting-on-dielectric (EWOD) have emerged as a promising platform in biomedical research, laboratory automation, and medical diagnostics. With these devices, researchers can manipulate micro-scale droplets and biological samples efficiently and precisely. This enables a wide range of experimental applications in disciplines such as biology, chemistry, and medicine.
Early breast cancer detection in CT scans using convolutional neural bidirectional feature pyramid network
Despite various approaches for detection and prevention, the incidence of human illnesses has progressively risen due to individual or environmental factors. Among these illnesses, cancer is the most prevalent global affliction, characterized by abnormal cell growth that impacts different body areas. Cancer manifests in various forms, including breast, prostate, lung, skin, and pancreatic cancer, and remains a leading cause of death worldwide (Rajinikanth et al., 2021).
Ruptured Sinus of Valsalva Aneurysm Diagnosed on Coronary Computed Tomography Angiography in a Patient With Trisomy 13 Syndrome
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A novel artificial intelligence-based predictive analytics technique to detect skin cancer
Introduction Skin cancer is brought on by malignant tumors, which develop when the proliferation of abnormal skin cells is left unchecked (Nandhini et al., 2021). The majority of cancer cases are caused by unprotected skin being exposed to UV radiation (Reichrath, 2020). Nowadays, 95 percent of skin malignancies diagnosed are squamous or carcinoma and 5 percent are melanomas (Daniels et al., 2020).
Predicting medical device failure: a promise to reduce healthcare facilities cost through smart healthcare management
Additional Information and Declarations Competing Interests The authors declare that they have no competing interests. Author Contributions Noorul Husna Abd Rahman conceived and designed the experiments, performed the experiments, analyzed the data, performed the computation work, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.
An attention embedded DUAL-LSTM method for financial risk early warning of the three new board-listed companies
Introduction New three board-listed companies’ financial risk prediction is a hot research point in the economic field. The financial risk early warning is to establish an early warning mechanism to predict the crisis for high-risk institutions with the intermittent change of economic and financial. The prediction models of the early financial risk are often math models that calculate by traditional statistics.
Reducing the economic burden in management of Guillain-Barre syndrome using modified plasmapheresis Iyer RR, Shah PH, Roy SK, Suri SK
Background: Guillain–Barre syndrome (GBS) is an autoimmune acute inflammatory demyelinating polyneuropathy affecting the peripheral nervous system treated with high-dose immunoglobulin, physical therapy, or plasmapheresis.
Reducing the economic burden in management of Guillain-Barre syndrome using modified plasmapheresis Iyer RR, Shah PH, Roy SK, Suri SK
Background: Guillain–Barre syndrome (GBS) is an autoimmune acute inflammatory demyelinating polyneuropathy affecting the peripheral nervous system treated with high-dose immunoglobulin, physical therapy, or plasmapheresis.
Reducing the economic burden in management of Guillain-Barre syndrome using modified plasmapheresis Iyer RR, Shah PH, Roy SK, Suri SK
Background: Guillain–Barre syndrome (GBS) is an autoimmune acute inflammatory demyelinating polyneuropathy affecting the peripheral nervous system treated with high-dose immunoglobulin, physical therapy, or plasmapheresis.
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