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1.
Breast Cancer ; 2024 Apr 15.
Artículo en Inglés | MEDLINE | ID: mdl-38619786

RESUMEN

BACKGROUND: Artificial Intelligence (AI) offers an approach to predictive modeling. The model learns to determine specific patterns of undesirable outcomes in a dataset. Therefore, a decision-making algorithm can be built based on these patterns to prevent negative results. This systematic review aimed to evaluate the usefulness of AI in breast reconstruction. METHODS: A systematic review was conducted in August 2022 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. MEDLINE, EMBASE, SCOPUS, and Google Scholar online databases were queried to capture all publications studying the use of artificial intelligence in breast reconstruction. RESULTS: A total of 23 studies were full text-screened after removing duplicates, and twelve articles fulfilled our inclusion criteria. The Machine Learning algorithms applied for neuropathic pain, lymphedema diagnosis, microvascular abdominal flap failure, donor site complications associated to muscle sparing Transverse Rectus Abdominis flap, surgical complications, financial toxicity, and patient-reported outcomes after breast surgery demonstrated that AI is a helpful tool to accurately predict patient results. In addition, one study used Computer Vision technology to assist in Deep Inferior Epigastric Perforator Artery detection for flap design, considerably reducing the preoperative time compared to manual identification. CONCLUSIONS: In breast reconstruction, AI can help the surgeon by optimizing the perioperative patients' counseling to predict negative outcomes, allowing execution of timely interventions and reducing the postoperative burden, which leads to obtaining the most successful results and improving patient satisfaction.

2.
J Adolesc Health ; 69(3): 398-405, 2021 09.
Artículo en Inglés | MEDLINE | ID: mdl-34452729

RESUMEN

PURPOSE: This study describes the results of an impact evaluation of the Linking Families and Teens (LiFT) program, a 5-hour program for families in rural communities. LiFT's goal is to reduce unplanned teen pregnancies by increasing family connectedness and youth's self-efficacy, knowledge, and sexual health skills. METHODS: LiFT was externally evaluated using a cluster randomized controlled trial. Families, consisting of one or more dyads of high school aged youth and their parenting adults, were randomly assigned to a study condition. The program was implemented 57 times in rural communities in 9 states. The analytic sample includes 786 youth (407 program and 379 control) with baseline, 3-month, and 12-month data. The analysis used an intent-to-treat framework using ordinary least squares regression to measure effects on each outcome. RESULTS: Fewer LiFT participants experienced a pregnancy than control youth, which was significant at 3 months (net of baseline, 0 program vs. 4 control) and marginally significant at 12 months (net of baseline, 6 program vs. 14 control.) At both follow-up periods, the program had statistically significant effects on youth's frequency of communication with their parenting adults about sexuality and pregnancy prevention and on their perceived competence to prevent pregnancy. CONCLUSIONS: LiFT achieved lasting effects on increasing parent-child communication and youth self-efficacy to prevent unwanted pregnancies a full year following the brief, family-focused workshop. LiFT's impact on pregnancy was significant at 3 months and trended in the right direction at 12 months. A larger experimental study of this promising program is warranted to show the long-term effect on pregnancy.


Asunto(s)
Embarazo en Adolescencia , Población Rural , Adolescente , Adulto , Niño , Comunicación , Femenino , Humanos , Relaciones Padres-Hijo , Padres , Embarazo , Embarazo en Adolescencia/prevención & control , Evaluación de Programas y Proyectos de Salud , Educación Sexual
3.
J Comp Neurol ; 467(1): 32-43, 2003 Dec 01.
Artículo en Inglés | MEDLINE | ID: mdl-14574678

RESUMEN

Defining the selective pattern of synapse replacement that occurs in different areas of the damaged brain is essential for predicting the limits of functional compensation that can be achieved after various types of brain injury. Here we describe the time course of dendritic reorganization, spine loss and recovery, and synapse replacement in the striatum following a unilateral cortex ablation. We found that the time course for the transient loss and recovery of dendritic spines on medium spiny I (MSI) neurons, the primary postsynaptic target for corticostriatal axons, paralleled the time course for the removal of degenerating axon terminals from the neuropil and the formation of new synapses on MSI neurons. Reinnervation of the deafferented striatum occurred chiefly by axon terminals that formed asymmetric synapses with dendritic spines of MSI neurons, and the mean density of asymmetric synapses recovered to 86% of the sham-operated rat value by 30 days postlesion. In addition, the synaptic circuitry of the reconstructed striatum was characterized by an increase in the number of multiple synaptic boutons (MSBs), i.e., presynaptic axon terminals that make contact with more than one dendritic spine. Whether the postsynaptic contacts of MSBs are formed with the dendritic spines of the same or a different parent dendrite in the striatum is unknown. Nevertheless, these data suggest that the formation of MSBs is an essential part of the compensatory response to the loss of input from the ipsilateral cortex following the aspiration lesion and may serve to modulate activity-dependent adaptive changes in the reconstructed striatum that can lead to functional recovery.


Asunto(s)
Corteza Cerebral , Cuerpo Estriado , Dendritas , Regeneración Nerviosa , Sinapsis , Animales , Corteza Cerebral/metabolismo , Corteza Cerebral/cirugía , Cuerpo Estriado/metabolismo , Dendritas/metabolismo , Dendritas/ultraestructura , Masculino , Microscopía Electrónica , Degeneración Nerviosa , Vías Nerviosas/metabolismo , Neuronas/metabolismo , Neuronas/ultraestructura , Neurópilo/metabolismo , Neurópilo/ultraestructura , Terminales Presinápticos/metabolismo , Terminales Presinápticos/ultraestructura , Ratas , Ratas Endogámicas F344 , Sinapsis/metabolismo , Sinapsis/ultraestructura , Factores de Tiempo
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