<p>Attribute-based searchable encryption (ABSE) facilitates encrypted search and doctors’ access control, playing a crucial role in privacy-preserving of electronic medical records (EMRs) for Internet of Medical Things (IoMT). Nevertheless, existing ABSE schemes are limited due to supporting a single keyword search. Conjunctive keyword search, which allows doctors to input a set of keywords to generate valid trapdoors, significantly enhances search precision. In addition, quantum computers seriously threaten the security of existing ABSE schemes, resulting in privacy leakage from EMRs. As a result, there is an immediate requirement to design a post-quantum ABSE scheme that provides conjunctive keyword search. To bridge this gap, we construct an attribute-based conjunctive encrypted search scheme over lattice for IoMT, named ACES. ACES simultaneously ensures access control and precise search, while resisting quantum computing attacks. Unlike existing ABKS schemes, we propose a novel secret key generation method that incorporates lattice basis generation and sampling algorithms to calculate a search trapdoor and decrypt the ciphertext. Additionally, we introduce a generalized lattice basis sampling algorithm to embed an interested keyword set into the search trapdoor. Moreover, we provide formal proof for the IND-CKA and IND-CPA security of ACES. Comprehensive performance evaluations demonstrate that ACES exhibits low computational overhead. Specifically, the computational overhead of the Encrypt and Decrypt algorithms in ACES is only 82.86% and 4.87% of those in other state-of-the-art schemes, respectively.</p>