Artificial Intelligence Medical Compendium

INTRODUCTION: Artificial intelligence is being deployed across the pharmaceutical value chain, yet returns have been inconsistent. One of the explanations for this inconsistency is the organizational focus on models rather than the data foundations n... read more 

Multi-omics integration can improve cancer subtyping, but modality informativeness and noise vary across cancer types and patients. Most graph methods for multi-omics data learn modality contributions within the downstream classification objective, l... read more 

Artificial intelligence (AI) is increasingly influencing dental diagnosis and clinical decision-making, yet many AI systems continue to represent disease and treatment outcomes through discrete categories. Although binary classification has contribut... read more 

BACKGROUND: Early identification of myasthenia gravis (MG) severe exacerbations that require intensive care unit (ICU) admission remains challenging due disease highly heterogeneous. Existing models seldom incorporate phenotype stratification, limiti... read more 

BackgroundArtificial intelligence (AI) is rapidly transforming healthcare delivery across multiple disciplines. Allied health professions-including diagnostic medical sonography (DMS), health informatics (HI), medical billing and coding (MBC), midwif... read more 

BACKGROUND: Sepsis-induced left ventricular (LV) dysfunction complicates fluid resuscitation, increasing the risk of pulmonary edema and worsening outcomes. Echocardiographic assessment is often delayed, and natriuretic peptides such as N-terminal pr... read more 

Atomically precise luminescent copper(i) coordination clusters have emerged as a sustainable, earth-abundant, and structurally versatile class of materials, offering a compelling alternative to noble-metal (Au, Ag) luminophores. This review comprehen... read more 

Heavy metal contamination poses a critical global health risk, affecting over 2.2 billion people and necessitating rapid, sensitive, and field-deployable detection technologies. Conventional analytical techniques such as ICP-MS and AAS, while highly ... read more 

Machine-learning models in chemistry are increasingly trained on values compiled from many published papers and are usually validated by splitting the records at random or by publication; the latter assumes that each publication is an independent exp... read more 

PRCIS: ChatGPT-o1 and DeepSeek-R1 demonstrated similar performance in answering frequently asked patient questions. However, limitations in reliability and high reading levels underscore the need for greater oversight and refinement to improve their ... read more