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Artificial Intelligence in Nutrition and Dietetics: A Comprehensive Review of Current Research

Background/Objectives: Artificial intelligence (AI) has emerged as a transformative force in healthcare, with nutrition and dietetics becoming key areas of application. AI technologies are being employed to enhance dietary assessment, personalize nutrition plans, manage chronic diseases, deliver virtual coaching, and support public health nutrition. This review aims to critically synthesize the current literature on AI applications in nutrition, identify research gaps, and outline directions for future developme…

Healthcare · Health

Evidence-backed problem

Determining groundwater quality and its associated human health risk using hydrochemical signatures and some machine learning techniques

Groundwater is a major source of domestic water in coastal Ghana, but its quality is increasingly threatened by salinisation, nutrient enrichment, geogenic mineralisation, and localised anthropogenic contamination. In addition to hydrochemical indices and multivariate statistics that have been used over the years to assess coastal water quality, this study has incorporated nonlinear machine learning and probabilistic risk assessment to enhance source discrimination and uncertainty-based health risk characterisat…

Health

Evidence-backed gain

Factors associated with attitudes towards artificial intelligence among medical students: roles of digital literacy, emotional intelligence, and AI-related perceptions

Artificial intelligence is increasingly used in health care and medical education. This study aimed to identify factors associated with medical students' attitudes towards artificial intelligence, with particular attention to digital literacy, emotional intelligence and artificial intelligence-related perceptions. This cross-sectional study was conducted between November 2025 and January 2026 among 358 medical students. Data were collected using an online questionnaire including sociodemographic items, the Trait…

Health

Both readings

TrialTriage, a Semiautonomous Prescreening Workflow for Resolving Ambiguity in Phase I Oncology Trial Eligibility: Development and Proof-of-Concept Study Using Synthetic Cases

Enrollment in phase I oncology trials remains low largely because potentially eligible patients are not identified and evaluated quickly enough. Current clinical trial matching systems can identify candidate patients from the electronic health record, but cases with missing or uncertain eligibility data are often routed for offline manual review. This delay impedes clarification and prolongs the final eligibility determination. This study evaluated TrialTriage, a semiautonomous system built on the n8n platform a…

Health

Evidence-backed gain

Machine learning-based prediction of postoperative nausea and vomiting after spinal anesthesia: A retrospective observational study

Postoperative nausea and vomiting (PONV) is a frequent and serious complication after surgery. PONV also reduces patient satisfaction with surgery under spinal anesthesia and increases medical costs due to prolonged hospitalization. The purpose of this study is to apply artificial intelligence (AI) machine learning analysis to identify risk factors for PONV in patients undergoing surgery with spinal anesthesia. This retrospective study used artificial intelligence to analyze data of adult patients (aged ≥20 year…

Health

Evidence-backed gain

Dynamic prediction of HIV-related incomplete immune reconstitution: A multicenter, large cohort study using advanced joint modeling

Incomplete immune reconstitution (IIR) is a serious complication affecting 10 to 40% of people living with HIV (PLWH) despite effective antiretroviral therapy, leading to increased morbidity and mortality. Current risk prediction models rely on single-time point measurements and lack dynamic assessment capabilities. We developed a dynamic joint prediction system for IIR risk (DJPSIIR) using Bayesian joint modeling to analyze longitudinal data from 21,862 PLWH across 31 Chinese provinces (2003-2024). The system i…

Health

Both readings

Evaluating Artificial Intelligence Translation Tools for Language Equivalence of Oncology-Informed Consent Forms From English to Spanish

Approximately 8% of the US population speaks primary languages other than English. Limited English proficiency (LEP) contributes to under-representation of Hispanic patients in oncology clinical trials. Although certified translation services exist, they are time-consuming and costly. Artificial intelligence (AI)-generated translations of informed consent forms (ICFs) could provide low-cost alternatives, but data on accuracy and safety remain limited. We evaluated language equivalence of English-to-Spanish trans…

Health

AI as a Therapist, Companion, and Romantic Partner: Emerging Roles, Benefits, and Risks for Mental Health in Participatory Medicine

The line between tool and companion was once obvious, but conversational AI is blurring it in ways few researchers anticipated. Large language model chatbots and purpose-built AI companion agents are now used by millions of people every day. They are not being used to simply retrieve information but, instead, to offer emotional support, help process personal distress, and sustain what many describe as genuine relationships. Research puts the scale of this shift in sharp relief as nearly half (48.7%) of individua…

Health

AI makes a feature film in 14 days: Higgsfield shares its $500,000 filmmaking process with creators

Higgsfield AI has released the full production pipeline behind its 95-minute AI-generated action film, allowing creators to access the prompts, character models and workflows used to make the movie. The startup says it completed the film in 14 days for $500,000.

Media & Arts

AI makes a feature film in 14 days: Higgsfield shares its $500,000 filmmaking process with creators

Suno Lost To GEMA: Why The Ruling Should Worry AI Music Companies

A German court ruled AI music company Suno infringed copyright by using works represented by GEMA without permission and downloaded songs by stream-ripping

Media & Arts

Suno Lost To GEMA: Why The Ruling Should Worry AI Music Companies

Game, set, Chat: how tennis players use AI to scout opponents and run their lives

Not so long ago, Emma Raducanu was on her phone when she found herself wondering what her comprehensive usage of ChatGPT said about her own character. “I use Chat a lot,” Raducanu says, laughing. “Every small thing I do it and I got this idea. So, you know how Spotify do a Spotify Wrapped? I asked ChatGPT to make me a Chat Wrapped, and it was giving me a rundown on my personality. “I was like: ‘It’s a little bit too accurate.’ It was very clear, very concise. No nonsense, straight into the question. I thought: ‘…

Sports

Game, set, Chat: how tennis players use AI to scout opponents and run their lives

Quality of AI-Generated Patient Education for Pre- and Post-Operative Tracheostomy Care

Objective To evaluate the accuracy, completeness, clarity, source transparency, and readability of leading AI chatbot responses to patient questions about tracheostomy and to determine whether AI tools can reliably support patient education where high-quality guidance is critical for safety. Study design Cross-sectional content analysis. Setting Virtual study environment using publicly accessible AI platforms, with expert evaluation conducted via Qualtrics-based distribution. Methods Twelve frequently asked ques…

Health

Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data

Background Early prediction of in-hospital mortality in critically ill patients can aid clinicians in optimizing treatment. The objective was to develop a multimodal deep learning model, using structured and unstructured clinical data, to predict in-hospital mortality risk among critically ill patients after their initial 24 hour intensive care unit (ICU) admission. Methods We used data from MIMIC-III, MIMIC-IV, eICU, and HiRID. A multimodal model was developed on the MIMIC datasets, featuring time series compon…

Health

Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data

The FERM guild: a differentially correlated microbial module drives hypertension via metabolic flux perturbations

Hypertension is a major risk factor for cardiovascular diseases, with changes in gut microbiota composition and function being closely associated with its onset and progression. However, the high inter-individual variability in gut microbiota complicates the identification of pathogenic mechanisms using traditional methods. In contrast, the smaller variability in gut microbial metabolites offers a more reliable and consistent basis for cross-individual comparisons. Parsimonious flux balance analysis (pFBA), inte…

Health

SolenopsisDetector: development of an automatic detection system for fire ants using computer vision and deep learning

Fire ants (Solenopsis spp. Westwood) pose a major ecological and economic threat, mainly due to the invasive potential of certain species. Current identification methods are highly dependent on taxonomic expertise, which can slow down decision-making. The development of an automated detection system could therefore support the identification process. We present SolenopsisDetector (SolenopD), an automated system for identifying Solenopsis ants using computer vision and deep learning. Following taxonomic practice,…

Science

SolenopsisDetector: development of an automatic detection system for fire ants using computer vision and deep learning