Artificial intelligence for medicine 2025: Navigating the endless frontier

The Innovation Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 100120 - 100120

Published: Jan. 1, 2025

<p>Artificial intelligence (AI) is driving transformative changes in the field of medicine, with its successful application relying on accurate data and rigorous quality standards. By integrating clinical information, pathology, medical imaging, physiological signals, omics data, AI significantly enhances precision research into disease mechanisms patient prognoses. technologies also demonstrate exceptional potential drug development, surgical automation, brain-computer interface (BCI) research. Through simulation biological systems prediction intervention outcomes, enables researchers to rapidly translate innovations practical applications. While challenges such as computational demands, software ethical considerations persist, future remains highly promising. plays a pivotal role addressing societal issues like low birth rates aging populations. can contribute mitigating rate through enhanced ovarian reserve evaluation, menopause forecasting, optimization Assisted Reproductive Technologies (ART), sperm analysis selection, endometrial receptivity fertility remote consultations. In posed by an population, facilitate development dementia models, cognitive health monitoring strategies, early screening systems, AI-driven telemedicine platforms, intelligent smart companion robots, environments for aging-in-place. profoundly shapes medicine.</p>

Language: Английский

---

Artificial intelligence for life sciences: A comprehensive guide and future trends

The Innovation Life, Journal Year: 2024, Volume and Issue: unknown, P. 100105 - 100105

Published: Jan. 1, 2024

<p>Artificial intelligence has had a profound impact on life sciences. This review discusses the application, challenges, and future development directions of artificial in various branches sciences, including zoology, plant science, microbiology, biochemistry, molecular biology, cell developmental genetics, neuroscience, psychology, pharmacology, clinical medicine, biomaterials, ecology, environmental science. It elaborates important roles aspects such as behavior monitoring, population dynamic prediction, microorganism identification, disease detection. At same time, it points out challenges faced by application data quality, black-box problems, ethical concerns. The are prospected from technological innovation interdisciplinary cooperation. integration Bio-Technologies (BT) Information-Technologies (IT) will transform biomedical research into AI for Science paradigm.</p>

Language: Английский

---

Factors associated with underweight, overweight, and obesity in Chinese children aged 3–14 years using ensemble learning algorithms

Journal of Global Health, Journal Year: 2025, Volume and Issue: 15

Published: Feb. 6, 2025

Factors underlying the development of childhood underweight, overweight, and obesity are not fully understood. Traditional models have drawbacks in handling large-scale, high-dimensional, nonlinear data. In this study, we aimed to identify factors responsible for using machine learning methods among Chinese children. Our study participants were children aged 3-14 from 30 kindergartens 26 schools Beijing Tangshan. Weight status was defined per World Health Organization criteria. We implemented three ensemble algorithms compared their performance ranked contributing by importance identified an optimal set. A user-friendly web application developed calculate predicted probability obesity. analysed data 18 503 3-14, including 1798 10 579 normal weight, 3257 2869 with Of all algorithms, random forest performed best, area under receiver operating characteristic reaching 0.759 0.806 0.849 obesity, other metrics also reinforcing algorithm. Further cumulative analyses showed that, set six included maternal body mass index (BMI), age, paternal BMI, reproductive birth weight. The overweight comprised five factors: fast food intake, sedentary time. For time, age. logistic regression confirmed predictive capability individual top factors. findings indicate that is best algorithm predicting years. significant each malnutrition incorporated them into a support study's findings.

Language: Английский

---

Role of MLIP in burn-induced sepsis and insights into sepsis-associated cancer progression

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 14, 2025

Introduction Burn-induced sepsis is a critical clinical challenge marked by systemic inflammation, immune dysregulation, and high mortality. Macrophage-driven inflammatory pathways are central to pathogenesis, while cell metabolic reprogramming plays key role in both cancer progression. Methods Bioinformatics analyses using GEO, TCGA, GTEx datasets identified MLIP-modulated genes linked responses prognosis. In vitro , LPS-stimulated HUVEC cells were used study MLIP’s effects on inflammation macrophage function through viability, ROS levels, cytokine expression, qRT-PCR, immunofluorescence assays. Results associated with immune-related cancer. Epigenetic analysis showed MLIP expression regulated promoter methylation chromatin accessibility. Prognostic revealed impact survival outcomes across types. reduced oxidative stress, hyperactivation. Conclusions regulates immune-metabolic dynamics burn-induced sepsis, influencing activity stress. Its suggests as potential therapeutic target linking modulation Further research evasion tumor metabolism may inform novel strategies.

Language: Английский

---

The Involvement of Serotonin in the Obesity Pathway—A Last Decade Systematic Review of the Literature

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(7), P. 3081 - 3081

Published: March 27, 2025

Obesity represents a complex, multifactorial syndrome that high burden for public health systems worldwide. Serotonin is an important factor in feeding behavior and weight regulation their interplay implies multiple mechanisms could explain the correlation with obesity, so understanding these interconnections essential developing targeted therapeutic strategies. A systematic review of literature was conducted using PubMed Scopus databases, articles published between 1 January 2015 December 2024, based on predefined inclusion exclusion criteria. After selection process, 22 studies were selected detailed analysis, focusing role serotonin obesity. significantly influences appetite control energy homeostasis through multiples pathways, including insulin resistance, high-fat diets, gut microbiota, low-grade inflammation, interferences tryptophan metabolism, psychiatric modifications, genetic alterations receptors, implications eating behavior, neurohormonal appetite. This highlights multidimensional characteristics serotonin-obesity association, along its significance metabolic pathologies. In order to develop more efficient methods managing future should concentrate serotonergic complex management strategies involving axis.

Language: Английский

---