Aims: Our aim was to differentiate patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively normal (CN) individuals and predict the progression from MCI to AD within a 3-year longitudinal follow-up. A newly developed Holo-Hilbert Spectral Analysis (HHSA) was applied to resting state EEG (rsEEG), and features were extracted and subjected to machine learning algorithms.
Methods: A total of 205 participants were recruited from three hospitals, with CN ( = 51, MMSE > 26), MCI ( = 42, CDR = 0.
Invasive fungal infections (IFIs) is an important complication for acute myeloid leukemia (AML) patients receiving induction chemotherapy. However, the epidemiological information is not clear in Southeastern Asia, an area of potential high incidences of IFIs. To clarify it, we enrolled 298 non-M3 adult AML patients receiving induction chemotherapy without systemic anti-fungal prophylaxis from Jan 2004 to Dec 2009, when we applied a prospective diagnostic and treatment algorithm for IFIs.
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