Results 101 to 110 of about 5,628,292 (261)
Language, and Then Language . . . [PDF]
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This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel +4 more
wiley +1 more source
In patients with malignant ureteral obstruction undergoing percutaneous nephrostomy, sarcopenia defined by a low psoas muscle index was independently associated with poor overall survival on multivariate Cox regression analysis, suggesting that preoperative assessment of psoas muscle index may aid prognostic stratification in this population.
Kota Shimokihara +3 more
wiley +1 more source
Cancer treatment is associated with measurable acceleration of biological aging across epigenetic, telomere, senescence, and immune biomarkers. However, biomarker validation and interventional strategies remain limited, especially in hematologic malignancies, underscoring the need for standardized multi‐omic aging assessments and adequately powered ...
Moataz Ellithi +3 more
wiley +1 more source
Students' Voices on Artificial Intelligence: Uncovering the Dependency Paradox in Academic Writing
The proliferation of AI tools in academic writing has transformed scholarly practices, yet limited research has addressed long-term consequences of AI dependency on cognitive autonomy.
Syilvia Mustanuri Jannah +8 more
doaj +1 more source
Language Models Model Language
Linguistic commentary on LLMs, heavily influenced by the theoretical frameworks of de Saussure and Chomsky, is often speculative and unproductive. Critics challenge whether LLMs can legitimately model language, citing the need for "deep structure" or "grounding" to achieve an idealized linguistic "competence." We argue for a radical shift in ...
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A Language Processor and a Sample Language
Submitted - postscript ...
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ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley +1 more source

