AIMC Topic: Machine Learning

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Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response.

Frontiers in immunology
INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical inter...

Detection of Vitiligo Through Machine Learning and Computer-Aided Techniques: A Systematic Review.

BioMed research international
Vitiligo is a chronic skin damage disease, triggered by differential melanocyte death. Vitiligo (0.5%-1% of the population) is one of the most severe skin conditions. In general, the foundation of the condition of vitiligo remains gradual patchy los...

Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society.

PloS one
Informal education via social media plays a crucial role in modern learning, offering self-directed and community-driven opportunities to gain knowledge, skills, and attitudes beyond traditional educational settings. These platforms provide access to...

A novel machine learning model for perimeter intrusion detection using intrusion image dataset.

PloS one
Perimeter Intrusion Detection Systems (PIDS) are crucial for protecting any physical locations by detecting and responding to intrusions around its perimeter. Despite the availability of several PIDS, challenges remain in detection accuracy and preci...

Recurrent pregnancy loss: risk factors and predictive modeling approaches.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
PURPOSE: This review aims to identify and analyze the risk factors associated with recurrent pregnancy loss (RPL) and to evaluate the effectiveness of various predictive models in estimating the risk of RPL. The review also explores recent advancemen...

How Users' Personality Traits Predict Sentiment Tendencies of User-Generated Content in Social Media: A Mixed Method of Configuration Analysis and Machine Learning.

Journal of personality
OBJECTIVE: Social media content created by users with different personality traits presents various sentiment tendencies, easily leading to irrational public opinion. This study aims to explore the relationships between users' personality traits and ...

A Machine Learning Model to Predict De Novo Hepatocellular Carcinoma Beyond Year 5 of Antiviral Therapy in Patients With Chronic Hepatitis B.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: This study aims to develop and validate a machine learning (ML) model predicting hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients after the first 5 years of entecavir (ETV) or tenofovir (TFV) therapy.

Photonic platform coupled with machine learning algorithms to detect pyrolysis products of crack cocaine in saliva: A proof-of-concept animal study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive detection of crack/cocaine and other bioactive compounds from its pyrolysis in saliva can provide an alternative for drug analysis in forensic toxicology. Therefore, a highly sensitive, fast, reagent-free, and sustainable approach wi...

Textbook outcome in liver surgery for intrahepatic cholangiocarcinoma: defining predictors of an optimal postoperative course using machine learning.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangiocarcinoma (ICC) by considering the implications of perioperative outcomes on overall survival (OS).

A meta-analysis of AI and machine learning in project management: Optimizing vaccine development for emerging viral threats in biotechnology.

International journal of medical informatics
OBJECTIVES: Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies across various industries, including healthcare, biotechnology, and vaccine development. These technologies offer immense potential to impr...