Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
A peer-reviewed review published May 14 2025 examined the integration of smart sensors and IoT in precision agriculture, detailing how soil and plant stress sensors provide real-time data that is analyzed via AI and ML on IoT platforms for remote monitoring and automated control.
Published September 23 2025 as a peer-reviewed review, the article surveys how AI is being applied across healthcare, from analyzing electronic health records and medical imaging to supporting drug discovery, predictive analytics, telemedicine and wearable biosensors, with emphasis on low-resource and remote settings.
On 2025-11-05, Applied Sciences published a comprehensive review of machine learning for financial fraud detection. The authors surveyed supervised, unsupervised and hybrid approaches across credit card, financial statement, insurance and money laundering fraud, reviewed datasets and metrics, and included two case studies applying supervised models to real-world banking data.
On 2026-01-13, a peer-reviewed integrative review in Diseases synthesized 2015-2025 literature on cardiovascular diseases as an interconnected continuum, examining how multi-omics data combined with AI-enabled imaging and digital tools are applied across seven major condition clusters.
In a peer-reviewed study published October 27, 2024, researchers interviewed nineteen individuals about using generative AI chatbots like ChatGPT for mental health. Participants described high engagement and meaningful support, organized into themes of emotional sanctuary, insightful guidance about relationships, joy of connection, and comparisons to human therapy.
As of its March 5 2026 publication, this narrative literature review surveyed how neural network architectures are used for real-time financial fraud detection, covering MLPs, LSTMs, CNNs, Autoencoders, GNNs and Transformers, and the production requirement to operate within sub-100-millisecond payment authorization pipelines, with examples from credit card networks and Brazil's PIX system.
A structured narrative review of literature from January 2015 to December 2025 examined AI for hypertension screening, diagnosis, risk stratification, treatment optimization and remote monitoring. It found ML models often outperformed conventional risk scores with AUCs of 0.75 to 0.90 and showed promise for personalized therapy and continuous monitoring.
This review examines generative AI-enabled synthetic relationships, defined as ongoing associations with AI companions designed to simulate human-like bonds, as a potential intervention for loneliness where traditional approaches face availability and scalability limits.
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